diff --git a/.latexmkrc b/.latexmkrc index a279e3c..73b50dc 100644 --- a/.latexmkrc +++ b/.latexmkrc @@ -19,7 +19,7 @@ # 3: dvi conversion, as specified by the $dvipdf variable (useless) # 4: lualatex, as specified by the $lualatex variable (best) # 5: xelatex, as specified by the $xelatex variable (second best) -$pdf_mode = 1; +$pdf_mode = 4; # Treat undefined references and citations as well as multiply defined references as # ERRORS instead of WARNINGS. @@ -39,12 +39,12 @@ $pdf_mode = 1; $warnings_as_errors = 0; # Show used CPU time. Looks like: https://tex.stackexchange.com/a/312224/120853 -$show_time = 1; +$show_time = 0; # Default is 5; we seem to need more owed to the complexity of the document. # Actual documents probably don't need this many since they won't use all features, # plus won't be compiling from cold each time. -$max_repeat=7; +$max_repeat=10; # --shell-escape option (execution of code outside of latex) is required for the #'svg' package. @@ -65,7 +65,8 @@ $max_repeat=7; set_tex_cmds("--shell-escape -interaction=nonstopmode --synctex=1 %O %S"); # Use default pdf viewer -$pdf_previewer = 'zathura'; +$pdf_update_method = 1; +$pdf_previewer = "zathura %O %S"; # option 2 is same as 1 (run biber when necessary), but also deletes the # regeneratable bbl-file in a clenaup (`latexmk -c`). 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a/figs/test_apa_stroke_result.png b/figs/test_apa_stroke_result.png new file mode 100644 index 0000000..becb198 Binary files /dev/null and b/figs/test_apa_stroke_result.png differ diff --git a/figs/test_bench_apa_alone.pdf b/figs/test_bench_apa_alone.pdf deleted file mode 100644 index cc7f2fb..0000000 Binary files a/figs/test_bench_apa_alone.pdf and /dev/null differ diff --git a/figs/test_bench_apa_alone.png b/figs/test_bench_apa_alone.png deleted file mode 100644 index 15c398b..0000000 Binary files a/figs/test_bench_apa_alone.png and /dev/null differ diff --git a/preamble.tex b/preamble.tex index d18dbd9..46484e0 100644 --- a/preamble.tex +++ b/preamble.tex @@ -25,8 +25,6 @@ % \renewcommand*{\bibfont}{\footnotesize} -\usepackage{fontawesome} - \usepackage{caption} \usepackage{subcaption} diff --git a/test-bench-apa.bib b/test-bench-apa.bib index e69de29..6107bb4 100644 --- a/test-bench-apa.bib +++ b/test-bench-apa.bib @@ -0,0 +1,46 @@ +@book{reza06_piezoel_trans_vibrat_contr_dampin, + author = {Reza, Moheimani and Andrew, Fleming}, + title = {Piezoelectric Transducers for Vibration Control and + Damping}, + year = 2006, + publisher = {Springer}, + address = {London}, + isbn = 9781846283314, +} + + + +@article{gustavsen99_ration_approx_frequen_domain_respon, + author = {Gustavsen, B.; Semlyen, A.}, + title = {Rational Approximation of Frequency Domain Responses By + Vector Fitting}, + journal = {IEEE Transactions on Power Delivery}, + volume = 14, + year = 1999, + doi = {10.1109/61.772353}, + url = {https://doi.org/10.1109/61.772353}, + issne = {1937-4208}, + issnp = {0885-8977}, + issue = 3, + month = 7, + page = {1052--1061}, + publisher = {IEEE}, + keywords = {Motors}, +} + + + +@article{souleille18_concep_activ_mount_space_applic, + author = {Souleille, Adrien and Lampert, Thibault and Lafarga, V and + Hellegouarch, Sylvain and Rondineau, Alan and Rodrigues, + Gon{\c{c}}alo and Collette, Christophe}, + title = {A Concept of Active Mount for Space Applications}, + journal = {CEAS Space Journal}, + volume = 10, + number = 2, + pages = {157--165}, + year = 2018, + publisher = {Springer}, + keywords = {parallel robot, iff}, +} + diff --git a/test-bench-apa.org b/test-bench-apa.org index ef9448f..5ee81f2 100644 --- a/test-bench-apa.org +++ b/test-bench-apa.org @@ -96,181 +96,65 @@ #+END_SRC * Notes :noexport: -- Prefix for figures/section/tables =test_bench_apa= -Add the following reports: -- [ ] [[file:~/Cloud/work-projects/ID31-NASS/matlab/test-bench-apa95ml/test-bench-apa95ml.org][test-bench-apa95ml]] +Prefix for figures/section/tables =test_apa= + +** Add the following reports +- [X] [[file:~/Cloud/work-projects/ID31-NASS/matlab/test-bench-apa95ml/test-bench-apa95ml.org][test-bench-apa95ml]] Maybe not useful + - [X] See if the IFF root locus has been measured with the APA300ML + *Yes* - [X] [[file:~/Cloud/work-projects/ID31-NASS/matlab/test-bench-apa300ml/test-bench-apa300ml.org][test-bench-apa300ml]] - Model (Section 1) - Basic measurements (dimensions, electrical, stroke, etc...) (Section 2) - Dynamical measurements (Section 3) - Simscape Model (Section 4) +** TODO [#B] Check things about resistor in parallel with the force sensor + +Verify that everything interesting to say about that is either done before in the thesis or in this report. + * Introduction :ignore: + +#+name: fig:test_apa_received +#+attr_latex: :width 0.7\linewidth +#+caption: Picture of 5 out of the 7 received APA300ML +[[file:figs/test_apa_received.jpg]] + The first goal is to characterize the APA300ML in terms of: - The, geometric features, electrical capacitance, stroke, hysteresis, spurious resonances. - This is performed in Section ref:sec:first_measurements. + This is performed in Section ref:sec:test_apa_basic_meas. - The dynamics from the generated DAC voltage (going to the voltage amplifiers and then applied on the actuator stacks) to the induced displacement, and to the measured voltage by the force sensor stack. Also the "actuator constant" and "sensor constant" are identified. - This is done in Section ref:sec:dynamical_meas_apa. + This is done in Section ref:sec:test_apa_dynamics. - Compare the measurements with the Simscape models (2DoF, Super-Element) in order to tuned/validate the models. - This is explained in Section ref:sec:simscape_bench_apa. + This is explained in Section ref:sec:test_apa_simscape. -#+name: tab:test_bench_apa_section_matlab_code +#+name: tab:test_apa_section_matlab_code #+caption: Report sections and corresponding Matlab files #+attr_latex: :environment tabularx :width 0.6\linewidth :align lX #+attr_latex: :center t :booktabs t -| *Sections* | *Matlab File* | -|----------------------------------+------------------------| -| Section ref:sec:test_bench_apa_ | =test_bench_apa_1_.m= | - -* Model of the Amplified Piezoelectric Actuator -<> -** Introduction :ignore: -The Amplified Piezoelectric Actuator (APA) used is the APA300ML from Cedrat technologies (Figure [[fig:apa300ML]]). - -#+name: fig:apa300ML -#+caption: Picture of the APA300ML -#+attr_latex: :width 0.8\linewidth -[[file:figs/apa300ML.png]] - -Two simscape models of the APA300ML are developed: -- Section ref:sec:apa_2dof_model: a simple 2 degrees of freedom (DoF) model -- Section ref:sec:apa_flexible_model: a "flexible" model using a "super-element" extracted from a Finite Element Model of the APA - -For both models, an "actuator constant" and a "sensor constant" are used. -These constants are used to link the electrical domain and the mechanical domain. -They are described in Section ref:sec:apa_constants. - -** Two Degrees of Freedom Model -<> - -The presented model is based on cite:souleille18_concep_activ_mount_space_applic and represented in Figure ref:fig:souleille18_model_piezo. - -#+name: fig:souleille18_model_piezo -#+caption: Picture of an APA100M from Cedrat Technologies. Simplified model of a one DoF payload mounted on such isolator -#+attr_latex: :width 0.6\linewidth -[[file:./figs/souleille18_model_piezo.png]] - -The parameters are described in Table ref:tab:souleille18_model_params. - -#+name: tab:souleille18_model_params -#+caption: Parameters used for the model of the APA 100M -#+attr_latex: :environment tabularx :width 0.6\linewidth :align lX -#+attr_latex: :center t :booktabs t :float t -| | *Meaning* | -|-------+----------------------------------------------------------------| -| $k_e$ | Stiffness used to adjust the pole of the isolator | -| $k_1$ | Stiffness of the metallic suspension when the stack is removed | -| $k_a$ | Stiffness of the actuator | -| $c_1$ | Added viscous damping | - -The model is shown again in Figure ref:fig:2dof_apa_model. -As will be shown in the next section, such model can be quite accurate in modelling the axial behavior of the APA. -However, it does not model the flexibility of the APA in the other directions. - -Therefore this model can be useful for quick simulations as it contains a very limited number of states, but when more complex dynamics of the APA is to be modelled, a flexible model will be used. - -#+name: fig:2dof_apa_model -#+attr_latex: :width 0.2\linewidth -#+caption: Schematic of the 2DoF model for the Amplified Piezoelectric Actuator -[[file:figs/2dof_apa_model.png]] - -** Flexible Model -<> - -In order to model with high accuracy the behavior of the APA, a flexible model can be used. - -The idea is to do a Finite element model of the structure, and to defined "remote points" as shown in Figure ref:fig:apa300ml_ansys. -Then, on the finite element software, a "super-element" can be extracted which consists of a mass matrix, a stiffness matrix, and the coordinates of the remote points. - -#+name: fig:apa300ml_ansys -#+caption: Remote points for the APA300ML (Ansys) -#+attr_latex: :width 0.3\linewidth -[[file:figs/mesh_APA.png]] - -This "super-element" can then be included in the Simscape model as shown in Figure ref:fig:figure_name. -The remotes points are defined as "frames" in Simscape, and the "super-element" can be connected with other Simscape elements (mechanical joints, masses, force actuators, etc..). - -#+name: fig:figure_name -#+caption: From a finite Element Model (Ansys, bottom left) is extract the mass and stiffness matrices that are then used on Simscape (right) -#+attr_latex: :width \linewidth -[[file:figs/super_element_simscape.png]] - -** Actuator and Sensor constants -<> - -On Simscape, we want to model both the actuator stacks and the sensors stack. -We therefore need to link the electrical domain (voltages, charges) with the mechanical domain (forces, strain). -To do so, we use the "actuator constant" and the "sensor constant". - -Consider a schematic of the Amplified Piezoelectric Actuator in Figure ref:fig:apa_model_schematic. - -#+name: fig:apa_model_schematic -#+caption: Amplified Piezoelectric Actuator Schematic -#+attr_latex: :width 0.5\linewidth -[[file:figs/apa_model_schematic.png]] - -A voltage $V_a$ applied to the actuator stacks will induce an actuator force $F_a$: -\begin{equation} - \boxed{F_a = g_a \cdot V_a} -\end{equation} - -A change of length $dl$ of the sensor stack will induce a voltage $V_s$: -\begin{equation} - \boxed{V_s = g_s \cdot dl} -\end{equation} - -The block-diagram model of the piezoelectric actuator is then as shown in Figure [[fig:apa-model-simscape-schematic]]. - -#+begin_src latex :file apa-model-simscape-schematic.pdf - \begin{tikzpicture} - \node[block={2.0cm}{2.0cm}, align=center] (model) at (0,0){Simscape\\Model}; - \node[block, left=1.0 of model] (ga){$g_a(s)$}; - \node[block, right=1.0 of model] (gs){$g_s(s)$}; - - \draw[<-] (ga.west) -- node[midway, above]{$V_a$} node[midway, below]{$[V]$} ++(-1.0, 0); - \draw[->] (ga.east) --node[midway, above]{$F_a$} node[midway, below]{$[N]$} (model.west); - \draw[->] (model.east) --node[midway, above]{$dl$} node[midway, below]{$[m]$} (gs.west); - \draw[->] (gs.east) -- node[midway, above]{$V_s$} node[midway, below]{$[V]$} ++(1.0, 0); - \end{tikzpicture} -#+end_src - -#+name: fig:apa-model-simscape-schematic -#+caption: Model of the APA with Simscape/Simulink -#+RESULTS: -[[file:figs/apa-model-simscape-schematic.png]] - -The constants $g_a$ and $g_s$ will be experimentally estimated. +| *Sections* | *Matlab File* | +|-------------------------------------+---------------------------| +| Section ref:sec:test_apa_basic_meas | =test_apa_1_basic_meas.m= | +| Section ref:sec:test_apa_dynamics | =test_apa_2_.m= | +| Section ref:sec:test_apa_simscape | =test_apa_3_.m= | * First Basic Measurements -<> +:PROPERTIES: +:header-args:matlab+: :tangle matlab/test_apa_1_basic_meas.m +:END: +<> ** Introduction :ignore: Before using the measurement bench to characterize the APA300ML, first simple measurements are performed: -- Section ref:sec:geometrical_measurements: the geometric tolerances of the interface planes are checked -- Section ref:sec:electrical_measurements: the capacitance of the stacks are measured -- Section ref:sec:stroke_measurements: the stroke of the APA are measured -- Section ref:sec:spurious_resonances: the "spurious" resonances of the APA are investigated -- Section ref:sec:spurious_resonances_struts: the "spurious" resonances of the struts are measured and compared with the FEM +- Section ref:sec:test_apa_geometrical_measurements: the geometric tolerances of the interface planes are checked +- Section ref:sec:test_apa_electrical_measurements: the capacitance of the piezoelectric stacks is measured +- Section ref:sec:test_apa_stroke_measurements: the stroke of each APA is measured +- Section ref:sec:test_apa_spurious_resonances: the "spurious" resonances of the APA are investigated -** Geometrical Measurements -:PROPERTIES: -:header-args:matlab+: :tangle matlab/basic_meas_geometrical.m -:END: -<> -*** Introduction :ignore: - -The received APA are shown in Figure ref:fig:received_apa. - -#+name: fig:received_apa -#+caption: Received APA -#+attr_latex: :width 0.9\linewidth -[[file:figs/received_apa.jpg]] - -*** Matlab Init :noexport:ignore: +** Matlab Init :noexport:ignore: #+begin_src matlab :tangle no :exports none :results silent :noweb yes :var current_dir=(file-name-directory buffer-file-name) <> #+end_src @@ -279,67 +163,61 @@ The received APA are shown in Figure ref:fig:received_apa. <> #+end_src -#+begin_src matlab -colors = colororder; +#+begin_src matlab :tangle no :noweb yes +<> #+end_src -#+begin_src matlab :tangle no -addpath('./matlab/mat/'); -addpath('./matlab/'); +#+begin_src matlab :eval no :noweb yes +<> #+end_src -#+begin_src matlab :eval no -addpath('./mat/'); +#+begin_src matlab :noweb yes +<> #+end_src -*** Measurement Setup +** Geometrical Measurements +<> -The flatness corresponding to the two interface planes are measured as shown in Figure ref:fig:flatness_meas_setup. +To measure the flatness of the two mechanical interfaces of the APA300ML, a small measurement bench is installed on top of a metrology granite with very good flatness. -#+name: fig:flatness_meas_setup -#+caption: Measurement Setup -#+attr_latex: :width 0.8\linewidth -[[file:figs/flatness_meas_setup.jpg]] +As shown in Figure ref:fig:test_apa_flatness_setup, the APA is fixed to a clamp while a measuring probe[fn:3] is used to measure the height of 4 points on each of the APA300ML interfaces. -*** Measurement Results +From the X-Y-Z coordinates of the measured 8 points, the flatness is estimated by best fitting[fn:4] a plane through all the points. + +#+name: fig:test_apa_flatness_setup +#+attr_latex: :width 0.4\linewidth +#+caption: Measurement setup for flatness estimation of the two mechanical interfaces +[[file:figs/test_apa_flatness_setup.png]] -The height (Z) measurements at the 8 locations (4 points by plane) are defined below. #+begin_src matlab %% Measured height for all the APA at the 8 locations -apa1 = 1e-6*[0, -0.5 , 3.5 , 3.5 , 42 , 45.5, 52.5 , 46]; -apa2 = 1e-6*[0, -2.5 , -3 , 0 , -1.5 , 1 , -2 , -4]; -apa3 = 1e-6*[0, -1.5 , 15 , 17.5 , 6.5 , 6.5 , 21 , 23]; -apa4 = 1e-6*[0, 6.5 , 14.5 , 9 , 16 , 22 , 29.5 , 21]; -apa5 = 1e-6*[0, -12.5, 16.5 , 28.5 , -43 , -52 , -22.5, -13.5]; -apa6 = 1e-6*[0, -8 , -2 , 5 , -57.5, -62 , -55.5, -52.5]; -apa7 = 1e-6*[0, 19.5 , -8 , -29.5, 75 , 97.5, 70 , 48]; -apa7b = 1e-6*[0, 9 , -18.5, -30 , 31 , 46.5, 16.5 , 7.5]; +apa1 = 1e-6*[0, -0.5 , 3.5 , 3.5 , 42 , 45.5, 52.5 , 46]; +apa2 = 1e-6*[0, -2.5 , -3 , 0 , -1.5 , 1 , -2 , -4]; +apa3 = 1e-6*[0, -1.5 , 15 , 17.5 , 6.5 , 6.5 , 21 , 23]; +apa4 = 1e-6*[0, 6.5 , 14.5 , 9 , 16 , 22 , 29.5 , 21]; +apa5 = 1e-6*[0, -12.5, 16.5 , 28.5 , -43 , -52 , -22.5, -13.5]; +apa6 = 1e-6*[0, -8 , -2 , 5 , -57.5, -62 , -55.5, -52.5]; +apa7 = 1e-6*[0, 9 , -18.5, -30 , 31 , 46.5, 16.5 , 7.5]; -apa = {apa1, apa2, apa3, apa4, apa5, apa6, apa7b}; -#+end_src +apa = {apa1, apa2, apa3, apa4, apa5, apa6, apa7}; -The X/Y Positions of the 8 measurement points are defined below. -#+begin_src matlab %% X-Y positions of the measurements points W = 20e-3; % Width [m] L = 61e-3; % Length [m] d = 1e-3; % Distance from border [m] l = 15.5e-3; % [m] -pos = [[-L/2 + d; W/2 - d], - [-L/2 + l - d; W/2 - d], - [-L/2 + l - d; -W/2 + d], - [-L/2 + d; -W/2 + d], - [L/2 - l + d; W/2 - d], - [L/2 - d; W/2 - d], - [L/2 - d; -W/2 + d], - [L/2 - l + d; -W/2 + d]]; -#+end_src +pos = [[-L/2 + d, W/2 - d]; + [-L/2 + l - d, W/2 - d]; + [-L/2 + l - d, -W/2 + d]; + [-L/2 + d, -W/2 + d]; + [L/2 - l + d, W/2 - d]; + [L/2 - d, W/2 - d]; + [L/2 - d, -W/2 + d]; + [L/2 - l + d, -W/2 + d]]'; -Finally, the flatness is estimated by fitting a plane through the 8 points using the =fminsearch= command. -#+begin_src matlab %% Using fminsearch to find the best fitting plane -apa_d = zeros(1, 7); +apa_d = zeros(1, 7); % Measured flatness of the APA for i = 1:7 fun = @(x)max(abs(([pos; apa{i}]-[0;0;x(1)])'*([x(2:3);1]/norm([x(2:3);1])))); x0 = [0;0;0]; @@ -348,16 +226,16 @@ for i = 1:7 end #+end_src -The obtained flatness are shown in Table ref:tab:flatness_meas. +The measured flatness, summarized in Table ref:tab:test_apa_flatness_meas, are within the specifications. #+begin_src matlab :exports results :results value table replace :tangle no :post addhdr(*this*) data2orgtable(1e6*apa_d', {'APA 1', 'APA 2', 'APA 3', 'APA 4', 'APA 5', 'APA 6', 'APA 7'}, {'*Flatness* $[\mu m]$'}, ' %.1f '); #+end_src -#+name: tab:flatness_meas -#+caption: Estimated flatness -#+attr_latex: :environment tabularx :width 0.25\linewidth :align lc -#+attr_latex: :center t :booktabs t :float t +#+name: tab:test_apa_flatness_meas +#+caption: Estimated flatness of the APA300ML interfaces +#+attr_latex: :environment tabularx :width 0.3\linewidth :align Xc +#+attr_latex: :center t :booktabs t #+RESULTS: | | *Flatness* $[\mu m]$ | |-------+----------------------| @@ -369,38 +247,30 @@ data2orgtable(1e6*apa_d', {'APA 1', 'APA 2', 'APA 3', 'APA 4', 'APA 5', 'APA 6', | APA 6 | 7.1 | | APA 7 | 18.7 | -#+begin_important -The measured flatness of the APA300ML interface planes are within the specifications. -#+end_important - ** Electrical Measurements -<> -*** Measurement Setup -#+begin_note -The capacitance of the stacks is measure with the [[https://www.gwinstek.com/en-global/products/detail/LCR-800][LCR-800 Meter]] ([[file:doc/DS_LCR-800_Series_V2_E.pdf][doc]]) shown in Figure [[fig:LCR_meter]]. -The excitation frequency is set to be 1kHz. -#+end_note +<> -#+name: fig:LCR_meter +From the documentation of the APA300ML, the total capacitance of the three stacks should be between $18\,\mu F$ and $26\,\mu F$ with a nominal capacitance of $20\,\mu F$. + +The capacitance of the piezoelectric stacks found in the APA300ML have been measured with the LCR meter[fn:1] shown in Figure ref:fig:test_apa_lcr_meter. +The two stacks used as an actuator and the stack used as a force sensor are measured separately. + +#+name: fig:test_apa_lcr_meter #+caption: LCR Meter used for the measurements -#+attr_latex: :width 0.9\linewidth -[[file:figs/LCR_meter.jpg]] +#+attr_latex: :width 0.6\linewidth +[[file:figs/test_apa_lcr_meter.jpg]] -*** Measured Capacitance -From the documentation of the APA300ML, the total capacitance of the three stacks should be between $18\mu F$ and $26\mu F$ with a nominal capacitance of $20\mu F$. -However, from the documentation of the stack themselves, it can be seen that the capacitance of a single stack should be $4.4\mu F$. -Clearly, the total capacitance of the APA300ML if more than just three times the capacitance of one stack. +The measured capacitance are summarized in Table ref:tab:test_apa_capacitance and the average capacitance of one stack is $\approx 5 \mu F$. +However, the measured capacitance of the stacks of "APA 3" is only half of the expected capacitance. +This may indicate a manufacturing defect. -#+begin_question -Could it be possible that the capacitance of the stacks increase that much when they are pre-stressed? -#+end_question +The measured capacitance is found to be lower than the specified one. +This may be due to the fact that the manufacturer measures the capacitance with large signals ($-20\,V$ to $150\,V$) while it was here measured with small signals. -The measured capacitance of the stacks are summarized in Table ref:tab:apa300ml_capacitance. - -#+name: tab:apa300ml_capacitance +#+name: tab:test_apa_capacitance #+caption: Capacitance measured with the LCR meter. The excitation signal is a sinus at 1kHz #+attr_latex: :environment tabularx :width 0.5\linewidth :align lcc -#+attr_latex: :center t :booktabs t :float t +#+attr_latex: :center t :booktabs t | | *Sensor Stack* | *Actuator Stacks* | |-------+----------------+-------------------| | APA 1 | 5.10 | 10.03 | @@ -411,210 +281,49 @@ The measured capacitance of the stacks are summarized in Table ref:tab:apa300ml_ | APA 6 | 4.99 | 9.91 | | APA 7 | 4.85 | 9.85 | -#+begin_important -From the measurements (Table ref:tab:apa300ml_capacitance), the capacitance of one stack is found to be $\approx 5 \mu F$. -#+end_important +** Stroke Measurement +<> -#+begin_warning -There is clearly a problem with APA300ML number 3 -The APA number 3 has ben sent back to Cedrat, and a new APA300ML has been shipped back. -#+end_warning +The goal is here to verify that the stroke of the APA300ML is as specified in the datasheet. +To do so, one side of the APA is fixed to the granite, and a displacement probe[fn:2] is located on the other side as shown in Figure ref:fig:test_apa_stroke_bench. -** Stroke measurement -:PROPERTIES: -:header-args:matlab+: :tangle matlab/basic_meas_stroke.m -:END: -<> -*** Introduction :ignore: -We here wish to estimate the stroke of the APA. +Then, the voltage across the two actuator stacks is varied from $-20\,V$ to $150\,V$ using a DAC and a voltage amplifier. +Note that the voltage is here slowly varied as the displacement probe has a very low measurement bandwidth (see Figure ref:fig:test_apa_stroke_bench, left). -To do so, one side of the APA is fixed, and a displacement probe is located on the other side as shown in Figure ref:fig:stroke_test_bench. - -Then, a voltage is applied on either one or two stacks using a DAC and a voltage amplifier. - -#+begin_note -Here are the documentation of the equipment used for this test bench: -- *Voltage Amplifier*: [[file:doc/PD200-V7-R1.pdf][PD200]] with a gain of 20 -- *16bits DAC*: [[file:doc/IO131-OEM-Datasheet.pdf][IO313 Speedgoat card]] -- *Displacement Probe*: [[file:doc/Millimar--3723046--BA--C1208-C1216-C1240--FR--2016-11-08.pdf][Millimar C1216 electronics]] and [[file:doc/tmp3m0cvmue_7888038c-cdc8-48d8-a837-35de02760685.pdf][Millimar 1318 probe]] -#+end_note - -#+name: fig:stroke_test_bench +#+name: fig:test_apa_stroke_bench #+caption: Bench to measured the APA stroke #+attr_latex: :width 0.9\linewidth -[[file:figs/stroke_test_bench.jpg]] +[[file:figs/test_apa_stroke_bench.jpg]] -From the documentation, the nominal stroke of the APA300ML is $304\,\mu m$. +The measured APA displacement is shown as a function of the applied voltage in Figure ref:fig:test_apa_stroke_result, right. -*** Matlab Init :noexport:ignore: -#+begin_src matlab :tangle no :exports none :results silent :noweb yes :var current_dir=(file-name-directory buffer-file-name) -<> -#+end_src +Typical hysteresis curves for piezoelectric stack actuators can be observed. +The measured stroke is approximately $250\,\mu m$ when using only two of the three stacks, which is enough for the current application. +This is even above what is specified as the nominal stroke in the data-sheet ($304\,\mu m$, therefore $\approx 200\,\mu m$ if only two stacks are used). -#+begin_src matlab :exports none :results silent :noweb yes -<> -#+end_src +It is clear from Figure ref:fig:test_apa_stroke_result that "APA 3" has an issue compared to the other units. +This confirms the abnormal electrical measurements made in Section ref:sec:test_apa_electrical_measurements. +This unit was send sent back to Cedrat and a new one was shipped back. +From now on, only the six APA that behave as expected will be used. #+begin_src matlab -colors = colororder; +%% Load the measured strokes +load('meas_apa_stroke.mat', 'apa300ml_2s') #+end_src -#+begin_src matlab :tangle no -addpath('./matlab/mat/'); -addpath('./matlab/'); -#+end_src - -#+begin_src matlab :eval no -addpath('./mat/'); -#+end_src - -*** Voltage applied on one stack - -Let's first look at the relation between the voltage applied to *one* stack to the displacement of the APA as measured by the displacement probe. - -#+begin_src matlab :exports none -%% Load the measurements -apa300ml_1s = {}; -for i = 1:7 - apa300ml_1s(i) = {load(['mat/stroke_apa_1stacks_' num2str(i) '.mat'], 't', 'V', 'd')}; -end -#+end_src - -#+begin_src matlab :exports none -%% Only take the data between t=2 and t=10 and reset the measured displacement at t=2 -for i = 1:7 - t = apa300ml_1s{i}.t; - apa300ml_1s{i}.d = apa300ml_1s{i}.d - mean(apa300ml_1s{i}.d(t > 1.9 & t < 2.0)); - apa300ml_1s{i}.d = apa300ml_1s{i}.d(t > 2.0 & t < 10.0); - apa300ml_1s{i}.V = apa300ml_1s{i}.V(t > 2.0 & t < 10.0); - apa300ml_1s{i}.t = apa300ml_1s{i}.t(t > 2.0 & t < 10.0); -end -#+end_src - -The applied voltage is shown in Figure ref:fig:apa_stroke_voltage_time. - -#+begin_src matlab :exports none -%% Applied voltage as a function of time +#+begin_src matlab :exports none :results none +%% Results of the measured APA stroke figure; -plot(apa300ml_1s{1}.t, 20*apa300ml_1s{1}.V) -xlabel('Time [s]'); ylabel('Voltage [V]'); -ylim([-20,160]); yticks([-20 0 20 40 60 80 100 120 140 160]); -#+end_src +tiledlayout(1, 2, 'TileSpacing', 'Compact', 'Padding', 'None'); -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_stroke_voltage_time.pdf', 'width', 'wide', 'height', 'normal'); -#+end_src +% Generated voltage across the two piezoelectric stack actuators to estimate the stroke of the APA300ML +ax1 = nexttile(); +plot(apa300ml_2s{1}.t - apa300ml_2s{1}.t(1), 20*apa300ml_2s{1}.V, 'k-') +xlabel('Time [s]'); ylabel('Voltage [V]') +ylim([-20, 160]) -#+name: fig:apa_stroke_voltage_time -#+caption: Applied voltage as a function of time -#+RESULTS: -[[file:figs/apa_stroke_voltage_time.png]] - -The obtained displacements for all the APA are shown in Figure ref:fig:apa_stroke_time_1s. -The displacement is set to zero at initial time when the voltage applied is -20V. - -#+begin_src matlab :exports none -%% Measured motion for all the APA300ML -figure; -hold on; -for i = 1:7 - plot(apa300ml_1s{i}.t, 1e6*apa300ml_1s{i}.d, 'DisplayName', sprintf('APA %i', i)) -end -hold off; -xlabel('Time [s]'); ylabel('Displacement [$\mu m$]') -legend('location', 'southeast', 'FontSize', 8) -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_stroke_time_1s.pdf', 'width', 'wide', 'height', 'normal'); -#+end_src - -#+name: fig:apa_stroke_time_1s -#+caption: Displacement as a function of time for all the APA300ML (only one stack is used as an actuator) -#+RESULTS: -[[file:figs/apa_stroke_time_1s.png]] - -Finally, the displacement is shown as a function of the applied voltage in Figure [[fig:apa_d_vs_V_1s]]. -We can clearly see that there is a problem with the APA 3. -Also, there is a large hysteresis. - -#+begin_src matlab :exports none -%% Displacement as a function of the applied voltage -figure; -hold on; -for i = 1:7 - plot(20*apa300ml_1s{i}.V, 1e6*apa300ml_1s{i}.d, 'DisplayName', sprintf('APA %i', i)) -end -hold off; -xlabel('Voltage [V]'); ylabel('Displacement [$\mu m$]') -legend('location', 'southwest', 'FontSize', 8) -xlim([-20, 160]); ylim([-140, 0]); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_d_vs_V_1s.pdf', 'width', 'wide', 'height', 'tall'); -#+end_src - -#+name: fig:apa_d_vs_V_1s -#+caption: Displacement as a function of the applied voltage (on only one stack) -#+RESULTS: -[[file:figs/apa_d_vs_V_1s.png]] - -#+begin_important -We can clearly confirm from Figure [[fig:apa_d_vs_V_1s]] that there is a problem with the APA number 3. -#+end_important - -*** Voltage applied on two stacks - -Now look at the relation between the voltage applied to the *two* other stacks to the displacement of the APA as measured by the displacement probe. - -#+begin_src matlab :exports none -%% Load the measurements -apa300ml_2s = {}; -for i = 1:7 - apa300ml_2s(i) = {load(['mat/stroke_apa_2stacks_' num2str(i) '.mat'], 't', 'V', 'd')}; -end -#+end_src - -#+begin_src matlab :exports none -%% Only take the data between t=2 and t=10 and reset the measured displacement at t=2 -for i = 1:7 - t = apa300ml_2s{i}.t; - apa300ml_2s{i}.d = apa300ml_2s{i}.d - mean(apa300ml_2s{i}.d(t > 1.9 & t < 2.0)); - apa300ml_2s{i}.d = apa300ml_2s{i}.d(t > 2.0 & t < 10.0); - apa300ml_2s{i}.V = apa300ml_2s{i}.V(t > 2.0 & t < 10.0); - apa300ml_2s{i}.t = apa300ml_2s{i}.t(t > 2.0 & t < 10.0); -end -#+end_src - -The obtained displacement is shown in Figure ref:fig:apa_stroke_time_2s. -The displacement is set to zero at initial time when the voltage applied is -20V. -#+begin_src matlab :exports none -%% Measured motion for all the APA300ML -figure; -hold on; -for i = 1:7 - plot(apa300ml_2s{i}.t, 1e6*apa300ml_2s{i}.d, 'DisplayName', sprintf('APA %i', i)) -end -hold off; -xlabel('Time [s]'); ylabel('Displacement [$\mu m$]') -legend('location', 'southeast', 'FontSize', 8) -ylim([-250, 0]); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_stroke_time_2s.pdf', 'width', 'wide', 'height', 'normal'); -#+end_src - -#+name: fig:apa_stroke_time_2s -#+caption: Displacement as a function of time for all the APA300ML (two stacks are used as actuators) -#+RESULTS: -[[file:figs/apa_stroke_time_2s.png]] - -Finally, the displacement is shown as a function of the applied voltage in Figure [[fig:apa_d_vs_V_2s]]. -#+begin_src matlab :exports none -%% Displacement as a function of the applied voltage -figure; +% Measured displacement as a function of the applied voltage +ax2 = nexttile(); hold on; for i = 1:7 plot(20*apa300ml_2s{i}.V, 1e6*apa300ml_2s{i}.d, 'DisplayName', sprintf('APA %i', i)) @@ -622,105 +331,32 @@ end hold off; xlabel('Voltage [V]'); ylabel('Displacement [$\mu m$]') legend('location', 'southwest', 'FontSize', 8) -xlim([-20, 160]); ylim([-250, 0]); +xlim([-20, 150]); ylim([-250, 0]); #+end_src #+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_d_vs_V_2s.pdf', 'width', 'wide', 'height', 'tall'); +exportFig('figs/test_apa_stroke_result.pdf', 'width', 'full', 'height', 'normal'); #+end_src -#+name: fig:apa_d_vs_V_2s -#+caption: Displacement as a function of the applied voltage on two stacks +#+name: fig:test_apa_stroke_result +#+caption: Generated voltage across the two piezoelectric stack actuators to estimate the stroke of the APA300ML (left). Measured displacement as a function of the applied voltage (right) #+RESULTS: -[[file:figs/apa_d_vs_V_2s.png]] +[[file:figs/test_apa_stroke_result.png]] -*** Voltage applied on all three stacks - -Finally, we can combine the two measurements to estimate the relation between the displacement and the voltage applied to the *three* stacks (Figure [[fig:apa_d_vs_V_3s]]). - -#+begin_src matlab :exports none -%% Motion induced by applying a voltage to the three stack is the sum to the previous two measured displacements -apa300ml_3s = {}; -for i = 1:7 - apa300ml_3s(i) = apa300ml_1s(i); - apa300ml_3s{i}.d = apa300ml_1s{i}.d + apa300ml_2s{i}.d; -end -#+end_src - -#+begin_src matlab :exports none -%% Displacement as a function of the applied voltage -figure; -hold on; -for i = 1:7 - plot(20*apa300ml_3s{i}.V, 1e6*apa300ml_3s{i}.d, 'DisplayName', sprintf('APA %i', i)) -end -hold off; -xlabel('Voltage [V]'); ylabel('Displacement [$\mu m$]') -legend('location', 'southwest', 'FontSize', 8) -xlim([-20, 160]); ylim([-400, 0]); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_d_vs_V_3s.pdf', 'width', 'wide', 'height', 'tall'); -#+end_src - -#+name: fig:apa_d_vs_V_3s -#+caption: Displacement as a function of the applied voltage on all three stacks -#+RESULTS: -[[file:figs/apa_d_vs_V_3s.png]] - -The obtained maximum stroke for all the APA are summarized in Table ref:tab:apa_measured_stroke. - -#+begin_src matlab :exports none -%% Estimate the maximum stroke -apa300ml_stroke = zeros(1, 7); -for i = 1:7 - apa300ml_stroke(i) = max(apa300ml_3s{i}.d) - min(apa300ml_3s{i}.d); -end -#+end_src - -#+begin_src matlab :exports results :results value table replace :tangle no :post addhdr(*this*) -data2orgtable(1e6*apa300ml_stroke', {'APA 1', 'APA 2', 'APA 3', 'APA 4', 'APA 5', 'APA 6', 'APA 7'}, {'*Stroke* $[\mu m]$'}, ' %.1f '); -#+end_src - -#+name: tab:apa_measured_stroke -#+caption: Measured maximum stroke -#+attr_latex: :environment tabularx :width 0.25\linewidth :align lc -#+attr_latex: :center t :booktabs t :float t -#+RESULTS: -| | *Stroke* $[\mu m]$ | -|-------+--------------------| -| APA 1 | 373.2 | -| APA 2 | 365.5 | -| APA 3 | 181.7 | -| APA 4 | 359.7 | -| APA 5 | 361.5 | -| APA 6 | 363.9 | -| APA 7 | 358.4 | - -*** Conclusion -#+begin_important -The except from APA 3 that has a problem, all the APA are similar when it comes to stroke and hysteresis. -Also, the obtained stroke is more than specified in the documentation. -Therefore, only two stacks can be used as an actuator. -#+end_important - -** Spurious resonances - APA -:PROPERTIES: -:header-args:matlab+: :tangle matlab/basic_meas_spurious_res.m -:END: -<> +** TODO Spurious resonances - APA :@philipp: +SCHEDULED: <2024-03-27 Wed> +<> *** Introduction -From a Finite Element Model of the struts, it have been found that three main resonances are foreseen to be problematic for the control of the APA300ML (Figure ref:fig:apa_mode_shapes_ter): +From a Finite Element Model of the struts, it have been found that three main resonances are foreseen to be problematic for the control of the APA300ML (Figure ref:fig:test_apa_mode_shapes): - Mode in X-bending at 189Hz - Mode in Y-bending at 285Hz - Mode in Z-torsion at 400Hz -#+name: fig:apa_mode_shapes_ter +#+name: fig:test_apa_mode_shapes #+caption: Spurious resonances. a) X-bending mode at 189Hz. b) Y-bending mode at 285Hz. c) Z-torsion mode at 400Hz #+attr_latex: :width \linewidth -[[file:figs/apa_mode_shapes.gif]] +[[file:figs/test_apa_mode_shapes.png]] These modes are present when flexible joints are fixed to the ends of the APA300ML. @@ -728,31 +364,9 @@ In this section, we try to find the resonance frequency of these modes when one In the section ref:sec:spurious_resonances_struts, a similar measurement will be performed directly on the struts. -*** Matlab Init :noexport:ignore: -#+begin_src matlab :tangle no :exports none :results silent :noweb yes :var current_dir=(file-name-directory buffer-file-name) -<> -#+end_src - -#+begin_src matlab :exports none :results silent :noweb yes -<> -#+end_src - -#+begin_src matlab -colors = colororder; -#+end_src - -#+begin_src matlab :tangle no -addpath('matlab/'); -addpath('matlab/mat/'); -#+end_src - -#+begin_src matlab :eval no -addpath('mat/'); -#+end_src - *** Measurement Setup -The measurement setup is shown in Figure ref:fig:measurement_setup_torsion. +The measurement setup is shown in Figure ref:fig:test_apa_meas_setup_torsion. A Laser vibrometer is measuring the difference of motion between two points. The APA is excited with an instrumented hammer and the transfer function from the hammer to the measured rotation is computed. @@ -762,21 +376,21 @@ The instrumentation used are: - Instrumented hammer #+end_note -#+name: fig:measurement_setup_torsion +#+name: fig:test_apa_meas_setup_torsion #+caption: Measurement setup with a Laser Doppler Vibrometer and one instrumental hammer #+attr_latex: :width 0.7\linewidth -[[file:figs/measurement_setup_torsion.jpg]] +[[file:figs/test_apa_meas_setup_torsion.jpg]] *** X-Bending Mode -The vibrometer is setup to measure the X-bending motion is shown in Figure [[fig:measurement_setup_X_bending]]. +The vibrometer is setup to measure the X-bending motion is shown in Figure ref:fig:test_apa_meas_setup_X_bending. The APA is excited with an instrumented hammer having a solid metallic tip. The impact point is on the back-side of the APA aligned with the top measurement point. -#+name: fig:measurement_setup_X_bending +#+name: fig:test_apa_meas_setup_X_bending #+caption: X-Bending measurement setup #+attr_latex: :width 0.7\linewidth -[[file:figs/measurement_setup_X_bending.jpg]] +[[file:figs/test_apa_meas_setup_X_bending.jpg]] The data is loaded. #+begin_src matlab @@ -788,16 +402,18 @@ The configuration (Sampling time and windows) for =tfestimate= is done: #+begin_src matlab %% Spectral Analysis setup Ts = bending_X.Track1_X_Resolution; % Sampling Time [s] -win = hann(ceil(1/Ts)); +Nfft = floor(1/Ts); +win = hanning(Nfft); +Noverlap = floor(Nfft/2); #+end_src The transfer function from the input force to the output "rotation" (difference between the two measured distances). #+begin_src matlab %% Compute the transfer function from applied force to measured rotation -[G_bending_X, f] = tfestimate(bending_X.Track1, bending_X.Track2, win, [], [], 1/Ts); +[G_bending_X, f] = tfestimate(bending_X.Track1, bending_X.Track2, win, Noverlap, Nfft, 1/Ts); #+end_src -The result is shown in Figure ref:fig:apa300ml_meas_freq_bending_x. +The result is shown in Figure ref:fig:test_apa_meas_freq_bending_x. The can clearly observe a nice peak at 280Hz, and then peaks at the odd "harmonics" (third "harmonic" at 840Hz, and fifth "harmonic" at 1400Hz). #+begin_src matlab :exports none @@ -815,29 +431,29 @@ text(1400, 7.0e-3,{'1400Hz'},'VerticalAlignment','bottom','HorizontalAlignment', #+end_src #+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa300ml_meas_freq_bending_x.pdf', 'width', 'wide', 'height', 'normal'); +exportFig('figs/test_apa_meas_freq_bending_x.pdf', 'width', 'wide', 'height', 'normal'); #+end_src -#+name: fig:apa300ml_meas_freq_bending_x +#+name: fig:test_apa_meas_freq_bending_x #+caption: Obtained FRF for the X-bending #+RESULTS: -[[file:figs/apa300ml_meas_freq_bending_x.png]] +[[file:figs/test_apa_meas_freq_bending_x.png]] -Then the APA is in the "free-free" condition, this bending mode is foreseen to be at 200Hz (Figure ref:fig:apa_mode_shapes_ter). +Then the APA is in the "free-free" condition, this bending mode is foreseen to be at 200Hz (Figure ref:fig:test_apa_mode_shapes). We are here in the "fixed-free" condition. If we consider that we therefore double the stiffness associated with this mode, we should obtain a resonance a factor $\sqrt{2}$ higher than 200Hz which is indeed 280Hz. Not sure this reasoning is correct though. *** Y-Bending Mode -The setup to measure the Y-bending is shown in Figure [[fig:measurement_setup_Y_bending]]. +The setup to measure the Y-bending is shown in Figure ref:fig:test_apa_meas_setup_Y_bending. The impact point of the instrumented hammer is located on the back surface of the top interface (on the back of the 2 measurements points). -#+name: fig:measurement_setup_Y_bending +#+name: fig:test_apa_meas_setup_Y_bending #+caption: Y-Bending measurement setup #+attr_latex: :width 0.7\linewidth -[[file:figs/measurement_setup_Y_bending.jpg]] +[[file:figs/test_apa_meas_setup_Y_bending.jpg]] The data is loaded, and the transfer function from the force to the measured rotation is computed. #+begin_src matlab @@ -845,10 +461,10 @@ The data is loaded, and the transfer function from the force to the measured rot bending_Y = load('apa300ml_bending_Y_top.mat'); %% Compute the transfer function -[G_bending_Y, ~] = tfestimate(bending_Y.Track1, bending_Y.Track2, win, [], [], 1/Ts); +[G_bending_Y, ~] = tfestimate(bending_Y.Track1, bending_Y.Track2, win, Noverlap, Nfft, 1/Ts); #+end_src -The results are shown in Figure ref:fig:apa300ml_meas_freq_bending_y. +The results are shown in Figure ref:fig:test_apa_meas_freq_bending_y. The main resonance is at 412Hz, and we also see the third "harmonic" at 1220Hz. #+begin_src matlab :exports none @@ -865,27 +481,27 @@ text(1218, 1.5e-2,{'1220Hz'},'VerticalAlignment','bottom','HorizontalAlignment', #+end_src #+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa300ml_meas_freq_bending_y.pdf', 'width', 'wide', 'height', 'normal'); +exportFig('figs/test_apa_meas_freq_bending_y.pdf', 'width', 'wide', 'height', 'normal'); #+end_src -#+name: fig:apa300ml_meas_freq_bending_y +#+name: fig:test_apa_meas_freq_bending_y #+caption: Obtained FRF for the Y-bending #+RESULTS: -[[file:figs/apa300ml_meas_freq_bending_y.png]] +[[file:figs/test_apa_meas_freq_bending_y.png]] We can apply the same reasoning as in the previous section and estimate the mode to be a factor $\sqrt{2}$ higher than the mode estimated in the "free-free" condition. We would obtain a mode at 403Hz which is very close to the one estimated here. *** Z-Torsion Mode -Finally, we measure the Z-torsion resonance as shown in Figure ref:fig:measurement_setup_torsion_bis. +Finally, we measure the Z-torsion resonance as shown in Figure ref:fig:test_apa_meas_setup_torsion_bis. The excitation is shown on the other side of the APA, on the side to excite the torsion motion. -#+name: fig:measurement_setup_torsion_bis +#+name: fig:test_apa_meas_setup_torsion_bis #+caption: Z-Torsion measurement setup #+attr_latex: :width 0.7\linewidth -[[file:figs/measurement_setup_torsion_bis.jpg]] +[[file:figs/test_apa_meas_setup_torsion_bis.jpg]] The data is loaded, and the transfer function computed. #+begin_src matlab @@ -893,10 +509,10 @@ The data is loaded, and the transfer function computed. torsion = load('apa300ml_torsion_left.mat'); %% Compute transfer function -[G_torsion, ~] = tfestimate(torsion.Track1, torsion.Track2, win, [], [], 1/Ts); +[G_torsion, ~] = tfestimate(torsion.Track1, torsion.Track2, win, Noverlap, Nfft, 1/Ts); #+end_src -The results are shown in Figure ref:fig:apa300ml_meas_freq_torsion_z. +The results are shown in Figure ref:fig:test_apa_meas_freq_torsion_z. We observe a first peak at 267Hz, which corresponds to the X-bending mode that was measured at 280Hz. And then a second peak at 415Hz, which corresponds to the X-bending mode that was measured at 412Hz. A third mode at 800Hz could correspond to this torsion mode. @@ -916,13 +532,13 @@ text(800, 6e-4,{'800Hz'}, 'VerticalAlignment', 'bottom','HorizontalAlignment','c #+end_src #+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa300ml_meas_freq_torsion_z.pdf', 'width', 'wide', 'height', 'normal'); +exportFig('figs/test_apa_meas_freq_torsion_z.pdf', 'width', 'wide', 'height', 'normal'); #+end_src -#+name: fig:apa300ml_meas_freq_torsion_z +#+name: fig:test_apa_meas_freq_torsion_z #+caption: Obtained FRF for the Z-torsion #+RESULTS: -[[file:figs/apa300ml_meas_freq_torsion_z.png]] +[[file:figs/test_apa_meas_freq_torsion_z.png]] In order to verify that, the APA is excited on the top part such that the torsion mode should not be excited. #+begin_src matlab @@ -930,10 +546,10 @@ In order to verify that, the APA is excited on the top part such that the torsio torsion = load('apa300ml_torsion_top.mat'); %% Compute transfer function -[G_torsion_top, ~] = tfestimate(torsion.Track1, torsion.Track2, win, [], [], 1/Ts); +[G_torsion_top, ~] = tfestimate(torsion.Track1, torsion.Track2, win, Noverlap, Nfft, 1/Ts); #+end_src -The two FRF are compared in Figure ref:fig:apa300ml_meas_freq_torsion_z_comp. +The two FRF are compared in Figure ref:fig:test_apa_meas_freq_torsion_z_comp. It is clear that the first two modes does not correspond to the torsional mode. Maybe the resonance at 800Hz, or even higher resonances. It is difficult to conclude here. #+begin_src matlab :exports none @@ -953,16 +569,16 @@ legend('location', 'northwest'); #+end_src #+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa300ml_meas_freq_torsion_z_comp.pdf', 'width', 'wide', 'height', 'normal'); +exportFig('figs/test_apa_meas_freq_torsion_z_comp.pdf', 'width', 'wide', 'height', 'normal'); #+end_src -#+name: fig:apa300ml_meas_freq_torsion_z_comp +#+name: fig:test_apa_meas_freq_torsion_z_comp #+caption: Obtained FRF for the Z-torsion #+RESULTS: -[[file:figs/apa300ml_meas_freq_torsion_z_comp.png]] +[[file:figs/test_apa_meas_freq_torsion_z_comp.png]] *** Compare -The three measurements are shown in Figure ref:fig:apa300ml_meas_freq_compare. +The three measurements are shown in Figure ref:fig:test_apa_meas_freq_compare. #+begin_src matlab :exports none figure; hold on; @@ -977,13 +593,13 @@ legend('location', 'southeast'); #+end_src #+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa300ml_meas_freq_compare.pdf', 'width', 'full', 'height', 'tall'); +exportFig('figs/test_apa_meas_freq_compare.pdf', 'width', 'full', 'height', 'tall'); #+end_src -#+name: fig:apa300ml_meas_freq_compare +#+name: fig:test_apa_meas_freq_compare #+caption: Obtained FRF - Comparison #+RESULTS: -[[file:figs/apa300ml_meas_freq_compare.png]] +[[file:figs/test_apa_meas_freq_compare.png]] *** Conclusion @@ -995,7 +611,7 @@ It is however quite interesting that there is a factor $\approx \sqrt{2}$ betwee #+name: tab:apa300ml_measured_modes_freq #+caption: Measured frequency of the modes -#+attr_latex: :environment tabularx :width 0.6\linewidth :align Xcc +#+attr_latex: :environment tabularx :width 0.7\linewidth :align Xcc #+attr_latex: :center t :booktabs t :float t | *Mode* | *FEM - Strut mode* | *Measured Frequency* | |-----------+--------------------+----------------------| @@ -1003,59 +619,62 @@ It is however quite interesting that there is a factor $\approx \sqrt{2}$ betwee | Y-Bending | 285Hz | 410Hz | | Z-Torsion | 400Hz | 800Hz? | +** Conclusion :ignore: + * Dynamical measurements - APA -<> +:PROPERTIES: +:header-args:matlab+: :tangle matlab/2_test_apa_dynamics.m +:END: +<> + ** Introduction :ignore: +After the basic measurements on the APA were performed in Section ref:sec:test_apa_basic_meas, a new test bench is used to better characterize the APA. -In this section, a measurement test bench is used to extract all the important parameters of the Amplified Piezoelectric Actuator APA300ML. +This test bench is shown in Figure ref:fig:test_bench_apa and consists of the APA300ML fixed on one end to the fixed granite, and on the other end to the 5kg granite vertically guided with an air bearing. +An encoder is used to measure the relative motion between the two granites (i.e. the displacement of the APA). -This include: -- Stroke -- Stiffness -- Hysteresis -- "Actuator constant": Gain from the applied voltage $V_a$ to the generated Force $F_a$ -- "Sensor constant": Gain from the sensor stack strain $\delta L$ to the generated voltage $V_s$ -- Dynamical behavior from the actuator to the force sensor and to the motion of the APA +#+name: fig:test_bench_apa +#+caption: Test bench used to characterize the APA300ML +#+begin_figure +#+attr_latex: :caption \subcaption{\label{fig:test_apa_bench_picture}Picture of the test bench} +#+attr_latex: :options {0.3\textwidth} +#+begin_subfigure +#+attr_latex: :height 8cm +[[file:figs/test_apa_bench_picture.jpg]] +#+end_subfigure +#+attr_latex: :caption \subcaption{\label{fig:test_apa_bench_picture_encoder}Zoom on the APA with the encoder} +#+attr_latex: :options {0.69\textwidth} +#+begin_subfigure +#+attr_latex: :height 8cm +[[file:figs/test_apa_bench_picture_encoder.jpg]] +#+end_subfigure +#+end_figure -The bench is shown in Figure ref:fig:picture_apa_bench, and a zoom picture on the APA and encoder is shown in Figure ref:fig:picture_apa_bench_encoder. +The bench is schematically shown in Figure ref:fig:test_apa_schematic and the signal used are summarized in Table ref:tab:test_apa_variables. -#+name: fig:picture_apa_bench -#+caption: Picture of the test bench -#+attr_latex: :width 0.5\linewidth -[[file:figs/picture_apa_bench.jpg]] - -#+name: fig:picture_apa_bench_encoder -#+caption: Zoom on the APA with the encoder -#+attr_latex: :width 0.5\linewidth -[[file:figs/picture_apa_bench_encoder.jpg]] - -The bench is schematically shown in Figure ref:fig:test_bench_apa_alone and the signal used are summarized in Table ref:tab:test_bench_apa_variables. - -#+name: fig:test_bench_apa_alone +#+name: fig:test_apa_schematic #+caption: Schematic of the Test Bench -#+attr_latex: :width 0.8\linewidth -[[file:figs/test_bench_apa_alone.png]] +#+attr_latex: :scale 1 +[[file:figs/test_apa_schematic.png]] -#+name: tab:test_bench_apa_variables +#+name: tab:test_apa_variables #+caption: Variables used during the measurements -#+attr_latex: :environment tabularx :width 0.9\linewidth :align lllX -#+attr_latex: :center t :booktabs t :float t -| *Variable* | *Description* | *Unit* | *Hardware* | -|------------+------------------------------+--------+-----------------------------| -| =Va= | Output DAC voltage | [V] | DAC - Ch. 1 - PD200 - APA | -| =Vs= | Measured stack voltage (ADC) | [V] | APA - ADC - Ch. 1 | -| =de= | Encoder Measurement | [m] | PEPU Ch. 1 - IO318(1) Ch. 1 | -| =da= | Attocube Measurement | [m] | PEPU Ch. 2 - IO318(1) Ch. 2 | -| =t= | Time | [s] | | +#+attr_latex: :environment tabularx :width 0.6\linewidth :align cXc +#+attr_latex: :center t :booktabs t +| *Variable* | *Description* | *Unit* | +|------------+------------------------------+--------| +| $u$ | Output DAC Voltage | $V$ | +| $V_a$ | Output Amplifier Voltage | $V$ | +| $V_s$ | Measured Stack Voltage (ADC) | $V$ | +| $d_e$ | Encoder Measurement | $m$ | -This section is structured as follows: -- Section ref:sec:meas_one_apa: the measurements are first performed on one APA. -- Section ref:sec:meas_all_apa: the same measurements are performed on all the APA and are compared. +This bench will be used to: +- measure the dynamics of the APA (from $V_a$ to $d_e$ and $d_a$ in Section ref:ssec:test_apa_meas_frf_disp, and from $V_a$ to $V_s$ in section ref:ssec:test_apa_meas_frf_force) +- estimate the added damping using Integral Force Feedback (Section ref:ssec:test_apa_iff_locus) -** Speedgoat Setup :noexport: -<> -*** Introduction :ignore: -*** Matlab Init :noexport:ignore: +These measurements will also be used to tune the model of the APA in Section ref:sec:test_apa_simscape. + +** Matlab Init :noexport:ignore: #+begin_src matlab :tangle no :exports none :results silent :noweb yes :var current_dir=(file-name-directory buffer-file-name) <> #+end_src @@ -1064,1217 +683,247 @@ This section is structured as follows: <> #+end_src -#+begin_src matlab -colors = colororder; +#+begin_src matlab :tangle no :noweb yes +<> #+end_src -#+begin_src matlab :tangle no -addpath('./matlab/src/'); -addpath('./matlab/'); +#+begin_src matlab :eval no :noweb yes +<> #+end_src -#+begin_src matlab :eval no -addpath('./src/'); +#+begin_src matlab :noweb yes +<> #+end_src -*** =frf_setup.m= - Measurement Setup -:PROPERTIES: -:header-args:matlab+: :tangle matlab/frf_setup.m -:END: -#+begin_src matlab :tangle no :exports none :results silent :noweb yes :var current_dir=(file-name-directory buffer-file-name) -<> -#+end_src +** Hysteresis +<> -#+begin_src matlab :exports none :results silent :noweb yes -<> -#+end_src +As the payload is vertically guided without friction, the hysteresis of the APA can be estimated from the motion of the payload. -#+begin_src matlab :eval no :exports none -addpath('./src/'); -#+end_src +A quasi static sinusoidal excitation $V_a$ with an offset of $65\,V$ (halfway between $-20\,V$ and $150\,V$), and an amplitude varying from $4\,V$ up to $80\,V$. -First is defined the sampling frequency: -#+begin_src matlab -%% Simulation configuration -Fs = 10e3; % Sampling Frequency [Hz] -Ts = 1/Fs; % Sampling Time [s] -#+end_src +For each excitation amplitude, the vertical displacement $d_e$ of the mass is measured and displayed as a function of the applied voltage.. -#+begin_src matlab -%% Data record configuration -Trec_start = 5; % Start time for Recording [s] -Trec_dur = 100; % Recording Duration [s] -#+end_src - -#+begin_src matlab -Tsim = 2*Trec_start + Trec_dur; % Simulation Time [s] -#+end_src - -A white noise excitation signal can be very useful in order to obtain a first idea of the plant FRF. -The gain can be gradually increased until satisfactory output is obtained. -#+begin_src matlab -%% Shaped Noise -V_noise = generateShapedNoise('Ts', 1/Fs, ... - 'V_mean', 3.25, ... - 't_start', Trec_start, ... - 'exc_duration', Trec_dur, ... - 'smooth_ends', true, ... - 'V_exc', 0.05/(1 + s/2/pi/10)); -#+end_src - -#+begin_src matlab :exports none :tangle no -figure; -tiledlayout(1, 2, 'TileSpacing', 'Normal', 'Padding', 'None'); - -ax1 = nexttile; -plot(V_noise(1,:), V_noise(2,:)); -xlabel('Time [s]'); ylabel('Amplitude [V]'); - -ax2 = nexttile; -win = hanning(floor(length(V_noise)/8)); -[pxx, f] = pwelch(V_noise(2,:), win, 0, [], Fs); -plot(f, pxx) -xlabel('Frequency [Hz]'); ylabel('Power Spectral Density [$V^2/Hz$]'); -set(gca, 'xscale', 'log'); set(gca, 'yscale', 'log'); -xlim([1, Fs/2]); ylim([1e-10, 1e0]); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/frf_meas_noise_excitation.pdf', 'width', 'full', 'height', 'normal'); -#+end_src - -#+name: fig:frf_meas_noise_excitation -#+caption: Example of Shaped noise excitation signal -#+RESULTS: -[[file:figs/frf_meas_noise_excitation.png]] - -The maximum excitation voltage at resonance is 9Vrms, therefore corresponding to 0.6V of output DAC voltage. -#+begin_src matlab -%% Sweep Sine -gc = 0.1; -xi = 0.5; -wn = 2*pi*94.3; - -% Notch filter at the resonance of the APA -G_sweep = 0.2*(s^2 + 2*gc*xi*wn*s + wn^2)/(s^2 + 2*xi*wn*s + wn^2); - -V_sweep = generateSweepExc('Ts', Ts, ... - 'f_start', 10, ... - 'f_end', 400, ... - 'V_mean', 3.25, ... - 't_start', Trec_start, ... - 'exc_duration', Trec_dur, ... - 'sweep_type', 'log', ... - 'V_exc', G_sweep*1/(1 + s/2/pi/500)); -#+end_src - -#+begin_src matlab :exports none :tangle no -figure; -tiledlayout(1, 2, 'TileSpacing', 'Normal', 'Padding', 'None'); - -ax1 = nexttile; -plot(V_sweep(1,:), V_sweep(2,:)); -xlabel('Time [s]'); ylabel('Amplitude [V]'); - -ax2 = nexttile; -win = hanning(floor(length(V_sweep(2,:))/80)); -[pxx, f] = pwelch(V_sweep(2,:), win, 0, [], Fs); -plot(f, pxx) -xlabel('Frequency [Hz]'); ylabel('Power Spectral Density [$V^2/Hz$]'); -set(gca, 'xscale', 'log'); set(gca, 'yscale', 'log'); -xlim([1, Fs/2]); ylim([1e-10, 1e0]); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/frf_meas_sweep_excitation.pdf', 'width', 'full', 'height', 'normal'); -#+end_src - -#+name: fig:frf_meas_sweep_excitation -#+caption: Example of Sweep Sin excitation signal -#+RESULTS: -[[file:figs/frf_meas_sweep_excitation.png]] - -In order to better estimate the high frequency dynamics, a band-limited noise can be used (Figure ref:fig:frf_meas_noise_hf_exc). -The frequency content of the noise can be precisely controlled. -#+begin_src matlab -%% High Frequency Shaped Noise -[b,a] = cheby1(10, 2, 2*pi*[300 2e3], 'bandpass', 's'); -wL = 0.005*tf(b, a); - -V_noise_hf = generateShapedNoise('Ts', 1/Fs, ... - 'V_mean', 3.25, ... - 't_start', Trec_start, ... - 'exc_duration', Trec_dur, ... - 'smooth_ends', true, ... - 'V_exc', wL); -#+end_src - -#+begin_src matlab :exports none :tangle no -figure; -tiledlayout(1, 2, 'TileSpacing', 'Normal', 'Padding', 'None'); - -ax1 = nexttile; -plot(V_noise_hf(1,:), V_noise_hf(2,:)); -xlabel('Time [s]'); ylabel('Amplitude [V]'); - -ax2 = nexttile; -win = hanning(floor(length(V_noise_hf(2,:))/80)); -[pxx, f] = pwelch(V_noise_hf(2,:), win, 0, [], Fs); -plot(f, pxx) -xlabel('Frequency [Hz]'); ylabel('Power Spectral Density [$V^2/Hz$]'); -set(gca, 'xscale', 'log'); set(gca, 'yscale', 'log'); -xlim([1, Fs/2]); ylim([1e-10, 1e0]); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/frf_meas_noise_hf_exc.pdf', 'width', 'wide', 'height', 'normal'); -#+end_src - -#+name: fig:frf_meas_noise_hf_exc -#+caption: Example of band-limited noise excitation signal -#+RESULTS: -[[file:figs/frf_meas_noise_hf_exc.png]] - - -Then a sinus excitation can be used to estimate the hysteresis. -#+begin_src matlab -%% Sinus excitation with increasing amplitude -V_sin = generateSinIncreasingAmpl('Ts', 1/Fs, ... - 'V_mean', 3.25, ... - 'sin_ampls', [0.1, 0.2, 0.4, 1, 2, 4], ... - 'sin_period', 1, ... - 'sin_num', 5, ... - 't_start', Trec_start, ... - 'smooth_ends', true); -#+end_src - -#+begin_src matlab :exports none :tangle no -figure; -plot(V_sin(1,:), V_sin(2,:)); -xlabel('Time [s]'); ylabel('Amplitude [V]'); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/frf_meas_sin_excitation.pdf', 'width', 'wide', 'height', 'normal'); -#+end_src - -#+name: fig:frf_meas_sin_excitation -#+caption: Example of Shaped noise excitation signal -#+RESULTS: -[[file:figs/frf_meas_sin_excitation.png]] - -Then, we select the wanted excitation signal. -#+begin_src matlab -%% Select the excitation signal -V_exc = timeseries(V_noise(2,:), V_noise(1,:)); -#+end_src - -#+begin_src matlab :exports none :eval no -%% Plot -figure; -tiledlayout(1, 2, 'TileSpacing', 'Normal', 'Padding', 'None'); - -ax1 = nexttile; -plot(V_exc(1,:), V_exc(2,:)); -xlabel('Time [s]'); ylabel('Amplitude [V]'); - -ax2 = nexttile; -win = hanning(floor(length(V_exc)/8)); -[pxx, f] = pwelch(V_exc(2,:), win, 0, [], Fs); -plot(f, pxx) -xlabel('Frequency [Hz]'); ylabel('Power Spectral Density [$V^2/Hz$]'); -set(gca, 'xscale', 'log'); set(gca, 'yscale', 'log'); -xlim([1, Fs/2]); ylim([1e-10, 1e0]); -#+end_src - -#+begin_src matlab -%% Save data that will be loaded in the Simulink file -save('./frf_data.mat', 'Fs', 'Ts', 'Tsim', 'Trec_start', 'Trec_dur', 'V_exc'); -#+end_src - -*** =frf_save.m= - Save Data -:PROPERTIES: -:header-args+: :tangle matlab/frf_save.m -:END: - -First, we get data from the Speedgoat: -#+begin_src matlab -tg = slrt; - -f = SimulinkRealTime.openFTP(tg); -mget(f, 'data/data.dat'); -close(f); -#+end_src - -And we load the data on the Workspace: -#+begin_src matlab -data = SimulinkRealTime.utils.getFileScopeData('data/data.dat').data; - -da = data(:, 1); % Excitation Voltage (input of PD200) [V] -de = data(:, 2); % Measured voltage (force sensor) [V] -Vs = data(:, 3); % Measurment displacement (encoder) [m] -Va = data(:, 4); % Measurement displacement (attocube) [m] -t = data(:, end); % Time [s] -#+end_src - -And we save this to a =mat= file: -#+begin_src matlab -apa_number = 1; - -save(sprintf('mat/frf_data_%i_huddle.mat', apa_number), 't', 'Va', 'Vs', 'de', 'da'); -#+end_src - -** Measurements on APA 1 -:PROPERTIES: -:header-args:matlab+: :tangle matlab/apa_meas_analysis_1.m -:END: -<> -*** Introduction :ignore: -Measurements are first performed on only *one* APA. -Once the measurement procedure is validated, it is performed on all the other APA. - -*** Matlab Init :noexport:ignore: -#+begin_src matlab :tangle no :exports none :results silent :noweb yes :var current_dir=(file-name-directory buffer-file-name) -<> -#+end_src - -#+begin_src matlab :exports none :results silent :noweb yes -<> -#+end_src - -#+begin_src matlab -colors = colororder; -Fs = 1e4; % Sampling Frequency [Hz] -Ts = 1/Fs; % Sampling Time [s] -#+end_src - -#+begin_src matlab :tangle no -addpath('./matlab/mat/'); -addpath('./matlab/src/'); -addpath('./matlab/'); -#+end_src - -#+begin_src matlab :eval no -addpath('./mat/'); -addpath('./src/'); -#+end_src - -*** Excitation Signals -Different excitation signals are used to perform FRF estimations. - -Typically, this is done in three steps: -1. A low pass filtered white noise is used with rather small amplitudes (Figure ref:fig:exc_signal_1_noise). - This first excitation is used to estimate the main resonance of the system. -2. A sweep-sine from 10Hz to 400Hz is used (Figure ref:fig:exc_signal_2_sweep). - The sweep-sine is is notched around the estimated resonance of the system. -3. A band-limited white noise from 300Hz to 2kHz is used to estimate the high frequency behavior (Figure ref:fig:exc_signal_3_hf_noise). - -For all the excitation signals, before the excitation starts, the mean voltage is slowly increased halfway between the minimum voltage (-20V) and the maximum (150V). - -The first measurement is only used to have a first estimation of the dynamics and verify that everything is setup correctly. -The second excitation is done to estimate the dynamics from 10Hz to 350Hz and the third excitation from 350Hz to 2kHz. -The second and third measurements are therefore combined in the frequency domain to form one good estimation of the dynamics from 10Hz up to 2kHz. - -#+begin_src matlab :exports none :tangle no -V_noise = generateShapedNoise('Ts', 1/Fs, ... - 'V_mean', 3.25, ... - 't_start', 5, ... - 'exc_duration', 50, ... - 'smooth_ends', true, ... - 'V_exc', 0.05/(1 + s/2/pi/10)); -#+end_src - -#+begin_src matlab :exports none :tangle no -%% Plot of the excitation signal and associated PSD -figure; -tiledlayout(1, 2, 'TileSpacing', 'Normal', 'Padding', 'None'); - -ax1 = nexttile; -plot(V_noise(1,:), V_noise(2,:)); -xlabel('Time [s]'); ylabel('Amplitude [V]'); - -ax2 = nexttile; -win = hanning(floor(length(V_noise(2,:))/8)); -[pxx, f] = pwelch(V_noise(2,:), win, 0, [], Fs); -plot(f, pxx) -xlabel('Frequency [Hz]'); ylabel('Power Spectral Density [$V^2/Hz$]'); -set(gca, 'xscale', 'log'); set(gca, 'yscale', 'log'); -xlim([1, Fs/2]); ylim([1e-8, 1e-2]); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/exc_signal_1_noise.pdf', 'width', 'wide', 'height', 'normal'); -#+end_src - -#+name: fig:exc_signal_1_noise -#+caption: Low pass filtered white noise. Time domain (left), Frequency domain (right) -#+RESULTS: -[[file:figs/exc_signal_1_noise.png]] - -#+begin_src matlab :exports none :tangle no -gc = 0.1; -xi = 0.5; -wn = 2*pi*94.3; - -% Notch filter at the resonance of the APA -G_sweep = 0.2*(s^2 + 2*gc*xi*wn*s + wn^2)/(s^2 + 2*xi*wn*s + wn^2); - -V_sweep = generateSweepExc('Ts', 1/Fs, ... - 'f_start', 10, ... - 'f_end', 400, ... - 'V_mean', 3.25, ... - 't_start', 5, ... - 'exc_duration', 50, ... - 'sweep_type', 'log', ... - 'V_exc', G_sweep*1/(1 + s/2/pi/500)); -#+end_src - -#+begin_src matlab :exports none :tangle no -%% Plot of the Sweep excitation signal -figure; -plot(V_sweep(1,:), V_sweep(2,:)); -xlabel('Time [s]'); ylabel('Amplitude [V]'); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/exc_signal_2_sweep.pdf', 'width', 'half', 'height', 'normal'); -#+end_src - -#+name: fig:exc_signal_2_sweep -#+caption: Sweep Sine with a decreased amplitude around the resonance of the APA -#+RESULTS: -[[file:figs/exc_signal_2_sweep.png]] - -#+begin_src matlab :exports none :tangle no -%% High Frequency Noise -[b,a] = cheby1(10, 2, 2*pi*[300 2e3], 'bandpass', 's'); -wL = 0.005*tf(b, a); - -V_noise_hf = generateShapedNoise('Ts', 1/Fs, ... - 'V_mean', 3.25, ... - 't_start', 5, ... - 'exc_duration', 40, ... - 'smooth_ends', true, ... - 'V_exc', wL); -#+end_src - -#+begin_src matlab :exports none :tangle no -%% Plot of the excitation signal and associated PSD -figure; -tiledlayout(1, 2, 'TileSpacing', 'Normal', 'Padding', 'None'); - -ax1 = nexttile; -plot(V_noise_hf(1,:), V_noise_hf(2,:)); -xlabel('Time [s]'); ylabel('Amplitude [V]'); - -ax2 = nexttile; -win = hanning(floor(length(V_noise_hf(2,:))/8)); -[pxx, f] = pwelch(V_noise_hf(2,:), win, 0, [], Fs); -plot(f, pxx) -xlabel('Frequency [Hz]'); ylabel('Power Spectral Density [$V^2/Hz$]'); -set(gca, 'xscale', 'log'); set(gca, 'yscale', 'log'); -xlim([1, Fs/2]); ylim([1e-8, 1e-2]); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/exc_signal_3_hf_noise.pdf', 'width', 'wide', 'height', 'normal'); -#+end_src - -#+name: fig:exc_signal_3_hf_noise -#+caption: Band-pass white noise. Time domain (left), Frequency domain (right) -#+RESULTS: -[[file:figs/exc_signal_3_hf_noise.png]] - -*** First Measurement -For this first measurement for the first APA, a basic logarithmic sweep is used between 10Hz and 2kHz. - -The data are loaded. -#+begin_src matlab -%% Load data -apa_sweep = load(sprintf('mat/frf_data_%i_sweep.mat', 1), 't', 'Va', 'Vs', 'da', 'de'); -#+end_src - -The initial time is set to zero. -#+begin_src matlab -%% Time vector -t = apa_sweep.t - apa_sweep.t(1) ; % Time vector [s] -#+end_src - -The excitation signal is shown in Figure ref:fig:apa_bench_exc_sweep. -It is a sweep sine from 10Hz up to 2kHz filtered with a notch centered with the main resonance of the system and a low pass filter. -#+begin_src matlab :exports none -%% Plot the excitation signal -figure; -plot(t, apa_sweep.Va) -xlabel('Time [s]'); ylabel('Excitation Voltage $V_a$ [V]'); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_bench_exc_sweep.pdf', 'width', 'wide', 'height', 'normal'); -#+end_src - -#+name: fig:apa_bench_exc_sweep -#+caption: Excitation voltage -#+RESULTS: -[[file:figs/apa_bench_exc_sweep.png]] - -*** FRF - Setup -Let's define the sampling time/frequency. -#+begin_src matlab -%% Sampling Frequency / Time -Ts = (t(end) - t(1))/(length(t)-1); % Sampling Time [s] -Fs = 1/Ts; % Sampling Frequency [Hz] -#+end_src - -Then we defined a "Hanning" windows that will be used for the spectral analysis: -#+begin_src matlab -win = hanning(ceil(1*Fs)); % Hannning Windows -#+end_src - -We get the frequency vector that will be the same for all the frequency domain analysis. -#+begin_src matlab -% Only used to have the frequency vector "f" -[~, f] = tfestimate(apa_sweep.Va, apa_sweep.de, win, [], [], 1/Ts); -#+end_src - -*** FRF - Encoder and Interferometer -In this section, the transfer function from the excitation voltage $V_a$ to the encoder measured displacement $d_e$ and interferometer measurement $d_a$. - -The coherence from $V_a$ to $d_e$ and from $V_a$ to $d_a$ are computed and shown in Figure ref:fig:apa_1_coh_dvf. -They are quite good from 10Hz up to 500Hz. -#+begin_src matlab -%% Compute the coherence -[enc_coh, ~] = mscohere(apa_sweep.Va, apa_sweep.de, win, [], [], 1/Ts); -[int_coh, ~] = mscohere(apa_sweep.Va, apa_sweep.da, win, [], [], 1/Ts); -#+end_src - -#+begin_src matlab :exports none -%% Plot the coherence -figure; -hold on; -plot(f, enc_coh, 'DisplayName', '$d_e/V_a$'); -plot(f, int_coh, 'DisplayName', '$d_a/V_a$'); -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); -xlabel('Frequency [Hz]'); ylabel('Coherence [-]'); -xlim([5, 5e3]); ylim([0, 1]); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_1_coh_dvf.pdf', 'width', 'normal', 'height', 'normal'); -#+end_src - -#+name: fig:apa_1_coh_dvf -#+caption: Coherence for the identification from $V_a$ to $d_e$ -#+RESULTS: -[[file:figs/apa_1_coh_dvf.png]] - -The transfer functions are then estimated and shown in Figure ref:fig:apa_1_frf_dvf. -#+begin_src matlab -%% TF - Encoder and interferometer -[frf_enc, ~] = tfestimate(apa_sweep.Va, apa_sweep.de, win, [], [], 1/Ts); -[frf_int, ~] = tfestimate(apa_sweep.Va, apa_sweep.da, win, [], [], 1/Ts); -#+end_src - -It is shown than both the encoder and interferometers are measuring the same dynamics up to $\approx 700\,Hz$. -Above that, it is possible that there is some flexible elements apart from the APA that is adding resonances into one or the other FRF. - -#+begin_src matlab :exports none -figure; -tiledlayout(3, 1, 'TileSpacing', 'None', 'Padding', 'None'); - -ax1 = nexttile([2,1]); -hold on; -plot(f, abs(frf_enc), 'color', colors(1, :), ... - 'DisplayName', 'Encoder'); -plot(f, abs(frf_int), 'color', colors(2, :), ... - 'DisplayName', 'Interferometer'); -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); -ylabel('Amplitude $d/V_a$ [m/V]'); set(gca, 'XTickLabel',[]); -hold off; -legend('location', 'northeast'); -ylim([1e-9, 1e-3]); - -ax2 = nexttile; -hold on; -plot(f, 180/pi*angle(frf_enc), 'color', colors(1, :)); -plot(f, 180/pi*angle(frf_int), 'color', colors(2, :)); -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); -xlabel('Frequency [Hz]'); ylabel('Phase [deg]'); -hold off; -yticks(-360:90:360); - -linkaxes([ax1,ax2],'x'); -xlim([10, 2e3]); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_1_frf_dvf.pdf', 'width', 'wide', 'height', 'tall'); -#+end_src - -#+name: fig:apa_1_frf_dvf -#+caption: Obtained transfer functions from $V_a$ to both $d_e$ and $d_a$ -#+RESULTS: -[[file:figs/apa_1_frf_dvf.png]] - -#+begin_important -The transfer functions obtained in Figure ref:fig:apa_1_frf_dvf are very close to what was expected: -- constant gain at low frequency -- resonance at around 100Hz which corresponds to the APA axial mode -- no further resonance up until high frequency ($\approx 700\,Hz$) at which points several elements of the test bench can induces resonances in the measured FRF - -However, it was not expected to observe a "double resonance" at around 95Hz (instead of only one resonance). -#+end_important - -*** FRF - Force Sensor -Now the dynamics from excitation voltage $V_a$ to the force sensor stack voltage $V_s$ is identified. - -The coherence is computed and shown in Figure ref:fig:apa_1_coh_iff and found very good from 10Hz up to 2kHz. -#+begin_src matlab -%% Compute the coherence from Va to Vs -[iff_coh, ~] = mscohere(apa_sweep.Va, apa_sweep.Vs, win, [], [], 1/Ts); -#+end_src - -#+begin_src matlab :exports none -%% Plot the coherence -figure; -hold on; -plot(f, iff_coh, 'k-'); -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); -xlabel('Frequency [Hz]'); ylabel('Coherence [-]'); -xlim([5, 5e3]); ylim([0, 1]); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_1_coh_iff.pdf', 'width', 'normal', 'height', 'normal'); -#+end_src - -#+name: fig:apa_1_coh_iff -#+caption: Coherence for the identification from $V_a$ to $V_s$ -#+RESULTS: -[[file:figs/apa_1_coh_iff.png]] - -The transfer function is estimated and shown in Figure ref:fig:apa_1_frf_iff. -#+begin_src matlab -%% Compute the TF from Va to Vs -[iff_sweep, ~] = tfestimate(apa_sweep.Va, apa_sweep.Vs, win, [], [], 1/Ts); -#+end_src - -#+begin_src matlab :exports none -%% Plot the TF -figure; -tiledlayout(3, 1, 'TileSpacing', 'None', 'Padding', 'None'); - -ax1 = nexttile([2,1]); -hold on; -plot(f, abs(iff_sweep), 'k-'); -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); -ylabel('Amplitude $V_s/V_a$ [V/V]'); set(gca, 'XTickLabel',[]); -hold off; -ylim([1e-2, 1e2]); - -ax2 = nexttile; -hold on; -plot(f, 180/pi*angle(iff_sweep), 'k-'); -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); -xlabel('Frequency [Hz]'); ylabel('Phase [deg]'); -hold off; -yticks(-360:90:360); - -linkaxes([ax1,ax2],'x'); -xlim([10, 2e3]); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_1_frf_iff.pdf', 'width', 'wide', 'height', 'tall'); -#+end_src - -#+name: fig:apa_1_frf_iff -#+caption: Obtained transfer functions from $V_a$ to $V_s$ -#+RESULTS: -[[file:figs/apa_1_frf_iff.png]] - -#+begin_important -The obtained dynamics from the excitation voltage $V_a$ to the measured sensor stack voltage $V_s$ is corresponding to what was expected: -- constant gain at low frequency -- complex conjugate zero and then complex conjugate pole -- constant gain at high frequency -#+end_important - -*** Hysteresis -We here wish to visually see the amount of hysteresis present in the APA. - -To do so, a quasi static sinusoidal excitation $V_a$ at different voltages is used. - -The offset is 65V (halfway between -20V and 150V), and the sin amplitude is ranging from 1V up to 80V (full range). - -For each excitation amplitude, the vertical displacement $d$ of the mass is measured. - -Then, $d$ is plotted as a function of $V_a$ for all the amplitudes. - -We expect to obtained something like the hysteresis shown in Figure ref:fig:expected_hysteresis. - -#+name: fig:expected_hysteresis -#+caption: Expected Hysteresis cite:poel10_explor_activ_hard_mount_vibrat -#+attr_latex: :width 0.8\linewidth -[[file:figs/expected_hysteresis.png]] - -The data is loaded. #+begin_src matlab %% Load measured data - hysteresis -apa_hyst = load('frf_data_1_hysteresis.mat', 't', 'Va', 'de'); +apa_hyst = load('frf_data_1_hysteresis.mat', 't', 'u', 'de'); + % Initial time set to zero apa_hyst.t = apa_hyst.t - apa_hyst.t(1); -#+end_src -The excitation voltage amplitudes are: -#+begin_src matlab ampls = [0.1, 0.2, 0.4, 1, 2, 4]; % Excitation voltage amplitudes #+end_src -The excitation voltage and the measured displacement are shown in Figure ref:fig:hyst_exc_signal_time. -#+begin_src matlab :exports none -%% Plot the excitation voltages and measured displacements -figure; -tiledlayout(1, 2, 'TileSpacing', 'None', 'Padding', 'None'); +The measured displacements as a function of the output voltages are shown in Figure ref:fig:test_apa_meas_hysteresis. +It is interesting to see that the hysteresis is increasing with the excitation amplitude. -ax1 = nexttile; -plot(apa_hyst.t, apa_hyst.Va) -xlabel('Time [s]'); ylabel('Output Voltage [V]'); - -ax2 = nexttile; -plot(apa_hyst.t, apa_hyst.de) -xlabel('Time [s]'); ylabel('Measured Displacement [m]'); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/hyst_exc_signal_time.pdf', 'width', 'full', 'height', 'normal'); -#+end_src - -#+name: fig:hyst_exc_signal_time -#+caption: Excitation voltage and measured displacement -#+RESULTS: -[[file:figs/hyst_exc_signal_time.png]] - -For each amplitude, we only take the last sinus in order to reduce possible transients. -Also, the motion is centered on zero. - -The measured displacement at a function of the output voltage are shown in Figure ref:fig:hyst_results_multi_ampl. #+begin_src matlab :exports none %% Measured displacement as a function of the output voltage figure; -tiledlayout(1, 3, 'TileSpacing', 'None', 'Padding', 'None'); -ax1 = nexttile([1,2]); hold on; -for i = flip(1:6) +for i = [6,5,4,2] i_lim = apa_hyst.t > i*5-1 & apa_hyst.t < i*5; - plot(apa_hyst.Va(i_lim) - mean(apa_hyst.Va(i_lim)), apa_hyst.de(i_lim) - mean(apa_hyst.de(i_lim)), ... - 'DisplayName', sprintf('$V_a = %.1f [V]$', ampls(i))) + plot(20*apa_hyst.u(i_lim), 1e6*detrend(apa_hyst.de(i_lim), 0), ... + 'DisplayName', sprintf('$V_a = 65 + %.0f \\sin (\\omega t) \\ [V]$', 20*ampls(i))) end hold off; -xlabel('Output Voltage [V]'); ylabel('Measured Displacement [m]'); -legend('location', 'northeast'); -xlim([-4, 4]); ylim([-1.2e-4, 1.2e-4]); - -ax2 = nexttile; -hold on; -for i = flip(1:6) - i_lim = apa_hyst.t > i*5-1 & apa_hyst.t < i*5; - plot(apa_hyst.Va(i_lim) - mean(apa_hyst.Va(i_lim)), apa_hyst.de(i_lim) - mean(apa_hyst.de(i_lim))) -end -hold off; -xlim([-0.4, 0.4]); ylim([-0.8e-5, 0.8e-5]); +xlabel('Stack Voltage $V_a$ [V]'); ylabel('Displacement $d_e$ [$\mu$m]'); +legend('location', 'northeast', 'FontSize', 8, 'NumColumns', 1); +xlim([-20, 150]); +ylim([-120, 120]); #+end_src #+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/hyst_results_multi_ampl.pdf', 'width', 'full', 'height', 'tall'); +exportFig('figs/test_apa_meas_hysteresis.pdf', 'width', 'wide', 'height', 'normal'); #+end_src -#+name: fig:hyst_results_multi_ampl -#+caption: Obtained hysteresis for multiple excitation amplitudes +#+name: fig:test_apa_meas_hysteresis +#+caption: Obtained hysteresis curves (displacement as a function of applied voltage) for multiple excitation amplitudes #+RESULTS: -[[file:figs/hyst_results_multi_ampl.png]] +[[file:figs/test_apa_meas_hysteresis.png]] -#+begin_important -From Figure ref:fig:hyst_results_multi_ampl, it is quite clear that hysteresis is increasing with the excitation amplitude. -For small excitation amplitudes ($V_a < 0.4\,V$) the hysteresis stays reasonably small. +** Axial stiffness +<> -Also, it is quite interesting to see that no hysteresis is found on the sensor stack voltage when using the same excitation signal. -#+end_important +In order to estimate the stiffness of the APA, a weight with known mass $m_a = 6.4\,\text{kg}$ is added on top of the suspended granite and the deflection $d_e$ is measured using the encoder. -*** Estimation of the APA axial stiffness -In order to estimate the stiffness of the APA, a weight with known mass $m_a$ is added on top of the suspended granite and the deflection $d_e$ is measured using the encoder. +The APA stiffness can then be estimated from equation eqref:eq:test_apa_stiffness. -The APA stiffness can then be estimated to be: -\begin{equation} - k_{\text{apa}} = \frac{m_a g}{d} +\begin{equation} \label{eq:test_apa_stiffness} + k_{\text{apa}} = \frac{m_a g}{\Delta d_e} \end{equation} -The data is loaded, and the measured displacement is shown in Figure ref:fig:apa_1_meas_stiffness. #+begin_src matlab %% Load data for stiffness measurement -apa_mass = load(sprintf('frf_data_%i_add_mass_closed_circuit.mat', 1), 't', 'de'); -apa_mass.de = apa_mass.de - mean(apa_mass.de(apa_mass.t<11)); -#+end_src - -#+begin_src matlab :exports none -%% Plot the deflection at a function of time -figure; -plot(apa_mass.t, apa_mass.de, 'k-'); -xlabel('Time [s]'); ylabel('Displacement $d_e$ [m]'); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_1_meas_stiffness.pdf', 'width', 'wide', 'height', 'normal'); -#+end_src - -#+name: fig:apa_1_meas_stiffness -#+caption: Measured displacement when adding the mass and removing the mass -#+RESULTS: -[[file:figs/apa_1_meas_stiffness.png]] - -From Figure ref:fig:apa_1_meas_stiffness, it can be seen that there are some drifts that are probably due to some creep. -This will induce some uncertainties in the measured stiffness. - -Here, a mass of 6.4 kg was used: -#+begin_src matlab -added_mass = 6.4; % Added mass [kg] -#+end_src - -The stiffness is then computed as follows: -#+begin_src matlab -k = 9.8 * added_mass / (mean(apa_mass.de(apa_mass.t > 12 & apa_mass.t < 12.5)) - mean(apa_mass.de(apa_mass.t > 20 & apa_mass.t < 20.5))); -#+end_src - -And the stiffness obtained is very close to the one specified in the documentation ($k = 1.794\,[N/\mu m]$). -#+begin_src matlab :results value replace :exports results :tangle no -sprintf('k = %.2f [N/um]', 1e-6*k); -#+end_src - -#+RESULTS: -: k = 1.68 [N/um] - -The stiffness could also be estimated based on the main vertical resonance of the system at $\omega_z = 2\pi \cdot 94 \,[rad/s]$. -The suspended mass is $m_{\text{sus}} = 5\,kg$. -And therefore, the axial stiffness of the APA can be estimated to be: -\begin{equation} -k_{\text{APA}} = m_{\text{sus}} \omega_z^2 -\end{equation} - -#+begin_src matlab -wz = 2*pi*94; % [rad/s] -msus = 5.7; % [kg] -k = msus * wz^2; -#+end_src - -#+begin_src matlab :results value replace :exports results :tangle no -sprintf('k = %.2f [N/um]', 1e-6*k); -#+end_src - -#+RESULTS: -: k = 1.99 [N/um] - -The two values are found relatively close to each other. -Anyway, the stiffness of the model will be tuned to match the measured FRF. - -*** Stiffness change due to electrical connections -Changes in the electrical impedance connected to the piezoelectric actuator causes changes in the mechanical compliance (or stiffness) of the piezoelectric actuator. - -In this section is measured the stiffness of the APA whether the piezoelectric actuator is connected to an open circuit or a short circuit (e.g. the output of a voltage amplifier). - -Note here that the resistor in parallel to the sensor stack is present in both cases. - -First, the data are loaded. -#+begin_src matlab -%% Load Data -add_mass_oc = load(sprintf('frf_data_%i_add_mass_open_circuit.mat', 1), 't', 'de'); -add_mass_cc = load(sprintf('frf_data_%i_add_mass_closed_circuit.mat', 1), 't', 'de'); -#+end_src - -And the initial displacement is set to zero. -#+begin_src matlab -%% Zero displacement at initial time -add_mass_oc.de = add_mass_oc.de - mean(add_mass_oc.de(add_mass_oc.t<11)); -add_mass_cc.de = add_mass_cc.de - mean(add_mass_cc.de(add_mass_cc.t<11)); -#+end_src - -The measured displacements are shown in Figure ref:fig:apa_meas_k_time_oc_cc. -#+begin_src matlab :exports none -figure; -hold on; -plot(add_mass_oc.t, add_mass_oc.de, 'DisplayName', 'Not connected'); -plot(add_mass_cc.t, add_mass_cc.de, 'DisplayName', 'Connected'); -hold off; -xlabel('Time [s]'); ylabel('Displacement $d_e$ [m]'); -legend('location', 'northeast'); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_meas_k_time_oc_cc.pdf', 'width', 'wide', 'height', 'normal'); -#+end_src - -#+name: fig:apa_meas_k_time_oc_cc -#+caption: Measured displacement -#+RESULTS: -[[file:figs/apa_meas_k_time_oc_cc.png]] - -And the stiffness is estimated in both case. -The results are shown in Table [[tab:APA_measured_k_oc_cc]]. -#+begin_src matlab -apa_k_oc = 9.8 * added_mass / (mean(add_mass_oc.de(add_mass_oc.t > 12 & add_mass_oc.t < 12.5)) - mean(add_mass_oc.de(add_mass_oc.t > 20 & add_mass_oc.t < 20.5))); -apa_k_cc = 9.8 * added_mass / (mean(add_mass_cc.de(add_mass_cc.t > 12 & add_mass_cc.t < 12.5)) - mean(add_mass_cc.de(add_mass_cc.t > 20 & add_mass_cc.t < 20.5))); -#+end_src - -#+begin_src matlab :exports results :results value table replace :tangle no :post addhdr(*this*) -data2orgtable(1e-6*[apa_k_oc; apa_k_cc], {'Not connected', 'Connected'}, {'$k [N/\mu m]$'}, ' %.1f '); -#+end_src - -#+name: tab:APA_measured_k_oc_cc -#+caption: Measured stiffnesses on "open" and "closed" circuits -#+attr_latex: :environment tabularx :width 0.3\linewidth :align cc -#+attr_latex: :center t :booktabs t :float t -#+RESULTS: -| | $k [N/\mu m]$ | -|---------------+---------------| -| Not connected | 2.3 | -| Connected | 1.7 | - -#+begin_important -Clearly, connecting the actuator stacks to the amplified (basically equivalent as to short circuiting them) lowers its stiffness. -#+end_important - -*** Effect of the resistor on the IFF Plant -A resistor $R \approx 80.6\,k\Omega$ is added in parallel with the sensor stack. -This has the effect to form a high pass filter with the capacitance of the stack. - -This is done for two reasons (explained in details [[file:../test-bench-force-sensor/test-bench-force-sensor.org][this document]]): -1. Limit the voltage offset due to the input bias current of the ADC -2. Limit the low frequency gain - -The (low frequency) transfer function from $V_a$ to $V_s$ with and without this resistor have been measured. - -#+begin_src matlab -%% Load the data -wi_k = load('frf_data_1_sweep_lf_with_R.mat', 't', 'Vs', 'Va'); % With the resistor -wo_k = load('frf_data_1_sweep_lf.mat', 't', 'Vs', 'Va'); % Without the resistor -#+end_src - -We use a very long "Hanning" window for the spectral analysis in order to estimate the low frequency behavior. -#+begin_src matlab -win = hanning(ceil(50*Fs)); % Hannning Windows -#+end_src - -And we estimate the transfer function from $V_a$ to $V_s$ in both cases: -#+begin_src matlab -%% Compute the transfer functions from Va to Vs -[frf_wo_k, f] = tfestimate(wo_k.Va, wo_k.Vs, win, [], [], 1/Ts); -[frf_wi_k, ~] = tfestimate(wi_k.Va, wi_k.Vs, win, [], [], 1/Ts); -#+end_src - -With the following values of the resistor and capacitance, we obtain a first order high pass filter with a crossover frequency equal to: -#+begin_src matlab -%% Model for the high pass filter -C = 5.1e-6; % Sensor Stack capacitance [F] -R = 80.6e3; % Parallel Resistor [Ohm] - -f0 = 1/(2*pi*R*C); % Crossover frequency of RC HPF [Hz] -#+end_src - -#+begin_src matlab :results value replace :exports results :tangle no -sprintf('f0 = %.2f [Hz]', f0) -#+end_src - -#+RESULTS: -: f0 = 0.39 [Hz] - -The transfer function of the corresponding high pass filter is: -#+begin_src matlab -G_hpf = 0.6*(s/2*pi*f0)/(1 + s/2*pi*f0); -#+end_src - -Let's compare the transfer function from actuator stack to sensor stack with and without the added resistor in Figure [[fig:frf_iff_effect_R]]. -#+begin_src matlab :exports none -%% Compare the HPF model and the measured FRF -figure; -tiledlayout(3, 1, 'TileSpacing', 'None', 'Padding', 'None'); - -ax1 = nexttile([2,1]); -hold on; -plot(f, abs(frf_wo_k), 'DisplayName', 'Without $k$'); -plot(f, abs(frf_wi_k), 'DisplayName', 'With $k$'); -plot(f, abs(squeeze(freqresp(G_hpf, f, 'Hz'))), 'k--', 'DisplayName', sprintf('HPF $f_o = %.2f [Hz]$', f0)); -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); -ylabel('Amplitude $V_{out}/V_{in}$ [V/V]'); set(gca, 'XTickLabel',[]); -hold off; -ylim([1e-1, 1e0]); -legend('location', 'southeast') - -ax2 = nexttile; -hold on; -plot(f, 180/pi*angle(frf_wo_k)); -plot(f, 180/pi*angle(frf_wi_k)); -plot(f, 180/pi*angle(squeeze(freqresp(G_hpf, f, 'Hz'))), 'k--'); -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); -xlabel('Frequency [Hz]'); ylabel('Phase [deg]'); -hold off; -yticks(-360:45:360); ylim([-45, 90]); - -linkaxes([ax1,ax2],'x'); -xlim([0.2, 8]); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/frf_iff_effect_R.pdf', 'width', 'wide', 'height', 'tall'); -#+end_src - -#+name: fig:frf_iff_effect_R -#+caption: Transfer function from $V_a$ to $V_s$ with and without the resistor $k$ -#+RESULTS: -[[file:figs/frf_iff_effect_R.png]] - -#+begin_important -The added resistor has indeed the expected effect of forming an high pass filter. -#+end_important - -** Comparison of all the APA -:PROPERTIES: -:header-args:matlab+: :tangle matlab/apa_meas_analysis_all.m -:END: -<> -*** Introduction :ignore: -The same measurements that was performed in Section ref:sec:meas_one_apa are now performed on all the APA and then compared. - -*** Matlab Init :noexport:ignore: -#+begin_src matlab :tangle no :exports none :results silent :noweb yes :var current_dir=(file-name-directory buffer-file-name) -<> -#+end_src - -#+begin_src matlab :exports none :results silent :noweb yes -<> -#+end_src - -#+begin_src matlab -colors = colororder; -#+end_src - -#+begin_src matlab :tangle no -addpath('./matlab/mat/'); -addpath('./matlab/src/'); -addpath('./matlab/'); -#+end_src - -#+begin_src matlab :eval no -addpath('./mat/'); -addpath('./src/'); -#+end_src - -*** Axial Stiffnesses - Comparison -Let's first compare the APA axial stiffnesses. - -The added mass is: -#+begin_src matlab -added_mass = 6.4; % Added mass [kg] -#+end_src - -Here are the numbers of the APA that have been measured: -#+begin_src matlab -apa_nums = [1 2 4 5 6 7 8]; -#+end_src - -The data are loaded. -#+begin_src matlab -%% Load Data +apa_nums = [1 2 4 5 6 8]; apa_mass = {}; for i = 1:length(apa_nums) apa_mass(i) = {load(sprintf('frf_data_%i_add_mass_closed_circuit.mat', apa_nums(i)), 't', 'de')}; % The initial displacement is set to zero apa_mass{i}.de = apa_mass{i}.de - mean(apa_mass{i}.de(apa_mass{i}.t<11)); end + +added_mass = 6.4; % Added mass [kg] #+end_src -The raw measurements are shown in Figure ref:fig:apa_meas_k_time. -All the APA seems to have similar stiffness except the APA 7 which show strange behavior. - -#+begin_warning -It is however strange that the displacement $d_e$ when the mass is removed is higher for the APA 7 than for the other APA. - -It turns out the PD200 amplifier was connected to only one stack, the other stack was open circuited. Therefore, the total axial stiffness of the APA was increased. -#+end_warning +The measured displacement $d_e$ as a function of time is shown in Figure ref:fig:test_apa_meas_stiffness_time. +It can be seen that there are some drifts in the measured displacement (probably due to piezoelectric creep) and the that displacement does not come back to the initial position after the mass is removed (probably due to piezoelectric hysteresis). +These two effects induce some uncertainties in the measured stiffness. #+begin_src matlab :exports none -%% Plot the time domain measured deflection +%% Plot the deflection at a function of time figure; hold on; -for i = 1:length(apa_nums) - plot(apa_mass{i}.t, apa_mass{i}.de, 'DisplayName', sprintf('APA %i', apa_nums(i))); -end +plot(apa_mass{2}.t(1:100:end)-apa_mass{2}.t(1), 1e6*apa_mass{2}.de(1:100:end), 'k-'); +plot([0,20], [-0.4, -0.4], 'k--', 'LineWidth', 0.5) +plot([0,20], [-4.5, -4.5], 'k--', 'LineWidth', 0.5) +plot([0,20], [-37.4, -37.4], 'k--', 'LineWidth', 0.5) +% first stroke for stiffness measurements +anArrow = annotation('doublearrow', 'LineWidth', 0.5); +anArrow.Parent = gca; +anArrow.Position = [2, -0.4, 0, -37]; +text(2.5, -20, sprintf('$d_1$'), 'horizontalalignment', 'left'); + +% second stroke for stiffness measurements +anArrow = annotation('doublearrow', 'LineWidth', 0.5); +anArrow.Parent = gca; +anArrow.Position = [18, -37.4, 0, 32.9]; +text(18.5, -20, sprintf('$d_2$'), 'horizontalalignment', 'left'); + +% annotation('textarrow',[],y,'String',' Growth ','FontSize',13,'Linewidth',2) hold off; -xlabel('Time [s]'); ylabel('Displacement $d_e$ [m]'); -legend('location', 'northeast', 'FontSize', 8, 'NumColumns', 2); +xlabel('Time [s]'); ylabel('Displacement $d_e$ [$\mu$m]'); #+end_src #+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_meas_k_time.pdf', 'width', 'wide', 'height', 'normal'); +exportFig('figs/test_apa_meas_stiffness_time.pdf', 'width', 'wide', 'height', 'normal'); #+end_src -#+name: fig:apa_meas_k_time -#+caption: Raw measurements for all the APA. A mass of 6.4kg is added at arround 15s and removed at arround 22s +#+name: fig:test_apa_meas_stiffness_time +#+caption: Measured displacement when adding the mass (at $t \approx 3\,s$) and removing the mass(at $t \approx 13\,s$) #+RESULTS: -[[file:figs/apa_meas_k_time.png]] +[[file:figs/test_apa_meas_stiffness_time.png]] -The stiffnesses are computed for all the APA and are summarized in Table [[tab:APA_measured_k]]. - -#+begin_src matlab :exports none -%% Compute the stiffness -apa_k = zeros(length(apa_nums), 1); -for i = 1:length(apa_nums) - apa_k(i) = 9.8 * added_mass / (mean(apa_mass{i}.de(apa_mass{i}.t > 12 & apa_mass{i}.t < 12.5)) - mean(apa_mass{i}.de(apa_mass{i}.t > 20 & apa_mass{i}.t < 20.5))); -end -#+end_src +The stiffnesses are computed for all the APA from the two displacements $d_1$ and $d_2$ (see Figure ref:fig:test_apa_meas_stiffness_time) leading to two stiffness estimations $k_1$ and $k_2$. +These estimated stiffnesses are summarized in Table ref:tab:test_apa_measured_stiffnesses and are found to be close to the nominal stiffness $k = 1.8\,N/\mu m$ found in the APA300ML manual. #+begin_src matlab :exports results :results value table replace :tangle no :post addhdr(*this*) - data2orgtable(1e-6*apa_k, cellstr(num2str(apa_nums')), {'APA Num', '$k [N/\mu m]$'}, ' %.2f '); + data2orgtable(1e-6*apa_k, cellstr(num2str(apa_nums')), {'APA', '$k_1$', '$k_2$'}, ' %.2f '); #+end_src -#+name: tab:APA_measured_k -#+caption: Measured stiffnesses -#+attr_latex: :environment tabularx :width 0.3\linewidth :align cc +#+name: tab:test_apa_measured_stiffnesses +#+caption: Measured stiffnesses (in $N/\mu m$) +#+attr_latex: :environment tabularx :width 0.2\linewidth :align ccc #+attr_latex: :center t :booktabs t :float t #+RESULTS: -| APA Num | $k [N/\mu m]$ | -|---------+---------------| -| 1 | 1.68 | -| 2 | 1.69 | -| 4 | 1.7 | -| 5 | 1.7 | -| 6 | 1.7 | -| 7 | 1.93 | -| 8 | 1.73 | +| APA | $k_1$ | $k_2$ | +|-----+-------+-------| +| 1 | 1.68 | 1.9 | +| 2 | 1.69 | 1.9 | +| 4 | 1.7 | 1.91 | +| 5 | 1.7 | 1.93 | +| 6 | 1.7 | 1.92 | +| 8 | 1.73 | 1.98 | -#+begin_important -The APA300ML manual specifies the nominal stiffness to be $1.8\,[N/\mu m]$ which is very close to what have been measured. -Only the APA number 7 is a little bit higher, due to the fact that one of the stack was open-circuited instead of short circuited. -#+end_important +The stiffness can also be computed using equation eqref:eq:test_apa_res_freq by knowing the main vertical resonance frequency $\omega_z \approx 94\,\text{Hz}$ (estimated by the dynamical measurements shown in section ref:ssec:test_apa_meas_frf_disp) and the suspended mass $m_{\text{sus}} = 5.7\,\text{kg}$. + +\begin{equation} \label{eq:test_apa_res_freq} +\omega_z = \sqrt{\frac{k}{m_{\text{sus}}}} +\end{equation} + +The obtain stiffness is $k \approx 2\,N/\mu m$ which is close to the values found in the documentation and by the "static deflection" method. + + +However, changes in the electrical impedance connected to the piezoelectric stacks impacts the mechanical compliance (or stiffness) of the piezoelectric stack [[cite:&reza06_piezoel_trans_vibrat_contr_dampin chap. 2]]. + +To estimate this effect, the stiffness of the APA if measured using the "static deflection" method in two cases: +- $k_{\text{os}}$: piezoelectric stacks left unconnected (or connect to the high impedance ADC) +- $k_{\text{sc}}$: piezoelectric stacks short circuited (or connected to the voltage amplifier with small output impedance) + +The open-circuit stiffness is estimated at $k_{\text{oc}} \approx 2.3\,N/\mu m$ and the closed-circuit stiffness $k_{\text{sc}} \approx 1.7\,N/\mu m$. -*** FRF - Setup -As the APA7 was not correctly wired, it is ignored: #+begin_src matlab -apa_nums = [1 2 4 5 6 8]; +%% Load Data +add_mass_oc = load('frf_data_1_add_mass_open_circuit.mat', 't', 'de'); +add_mass_cc = load('frf_data_1_add_mass_closed_circuit.mat', 't', 'de'); + +%% Zero displacement at initial time +add_mass_oc.de = add_mass_oc.de - mean(add_mass_oc.de(add_mass_oc.t<11)); +add_mass_cc.de = add_mass_cc.de - mean(add_mass_cc.de(add_mass_cc.t<11)); + +%% Estimation of the stiffness in Open Circuit and Closed-Circuit +apa_k_oc = 9.8 * added_mass / (mean(add_mass_oc.de(add_mass_oc.t > 12 & add_mass_oc.t < 12.5)) - mean(add_mass_oc.de(add_mass_oc.t > 20 & add_mass_oc.t < 20.5))); +apa_k_sc = 9.8 * added_mass / (mean(add_mass_cc.de(add_mass_cc.t > 12 & add_mass_cc.t < 12.5)) - mean(add_mass_cc.de(add_mass_cc.t > 20 & add_mass_cc.t < 20.5))); + +%% Estimated coupling factor +sqrt(1 - apa_k_sc/apa_k_oc) #+end_src -The identification is performed in three steps: -1. White noise excitation with small amplitude. - This is used to determine the main resonance of the system. -2. Sweep sine excitation with the amplitude lowered around the resonance. - The sweep sine is from 10Hz to 400Hz. -3. High frequency noise. - The noise is band-passed between 300Hz and 2kHz. +** Dynamics +<> -Then, the result of the second identification is used between 10Hz and 350Hz and the result of the third identification if used between 350Hz and 2kHz. +In this section, the dynamics of the system from the excitation voltage $u$ to encoder measured displacement $d_e$ and to the force sensor voltage $V_s$ is identified. -The data are loaded for both the second and third identification: #+begin_src matlab -%% Second identification -apa_sweep = {}; -for i = 1:length(apa_nums) - apa_sweep(i) = {load(sprintf('frf_data_%i_sweep.mat', apa_nums(i)), 't', 'Va', 'Vs', 'de', 'da')}; -end +%% Identification using sweep sine (low frequency) +load('frf_data_sweep.mat'); +load('frf_data_noise_hf.mat'); -%% Third identification -apa_noise_hf = {}; -for i = 1:length(apa_nums) - apa_noise_hf(i) = {load(sprintf('frf_data_%i_noise_hf.mat', apa_nums(i)), 't', 'Va', 'Vs', 'de', 'da')}; -end -#+end_src - -The time is the same for all measurements. -#+begin_src matlab -%% Time vector -t = apa_sweep{1}.t - apa_sweep{1}.t(1) ; % Time vector [s] - -%% Sampling -Ts = (t(end) - t(1))/(length(t)-1); % Sampling Time [s] +%% Sampling Frequency +Ts = 1e-4; % Sampling Time [s] Fs = 1/Ts; % Sampling Frequency [Hz] -#+end_src -Then we defined a "Hanning" windows that will be used for the spectral analysis: -#+begin_src matlab -win = hanning(ceil(0.5*Fs)); % Hannning Windows -#+end_src +%% "Hanning" windows used for the spectral analysis: +Nfft = floor(2/Ts); +win = hanning(Nfft); +Noverlap = floor(Nfft/2); -We get the frequency vector that will be the same for all the frequency domain analysis. -#+begin_src matlab +%% Separation of frequencies: low freqs using sweep sine, and high freq using noise % Only used to have the frequency vector "f" -[~, f] = tfestimate(apa_sweep{1}.Va, apa_sweep{1}.de, win, [], [], 1/Ts); +[~, f] = tfestimate(apa_sweep{1}.u, apa_sweep{1}.de, win, Noverlap, Nfft, 1/Ts); i_lf = f <= 350; i_hf = f > 350; -#+end_src -*** FRF - Encoder and Interferometer -In this section, the dynamics from excitation voltage $V_a$ to encoder measured displacement $d_e$ is identified. - -We compute the coherence for 2nd and 3rd identification: -#+begin_src matlab -%% Coherence computation -coh_enc = zeros(length(f), length(apa_nums)); -for i = 1:length(apa_nums) - [coh_lf, ~] = mscohere(apa_sweep{i}.Va, apa_sweep{i}.de, win, [], [], 1/Ts); - [coh_hf, ~] = mscohere(apa_noise_hf{i}.Va, apa_noise_hf{i}.de, win, [], [], 1/Ts); - coh_enc(:, i) = [coh_lf(i_lf); coh_hf(i_hf)]; -end -#+end_src - -The coherence is shown in Figure ref:fig:apa_frf_dvf_plant_coh, and it is found that the coherence is good from low frequency up to 700Hz. - -#+begin_src matlab :exports none -figure; -hold on; -for i = 1:length(apa_nums) - plot(f, coh_enc(:, i), ... - 'DisplayName', sprintf('APA %i', apa_nums(i))); -end; -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); -xlabel('Frequency [Hz]'); ylabel('Coherence [-]'); -xlim([5, 5e3]); ylim([0, 1]); -legend('location', 'southwest', 'FontSize', 8, 'NumColumns', 2); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_frf_dvf_plant_coh.pdf', 'width', 'wide', 'height', 'normal'); -#+end_src - -#+name: fig:apa_frf_dvf_plant_coh -#+caption: Obtained coherence for the plant from $V_a$ to $d_e$ -#+RESULTS: -[[file:figs/apa_frf_dvf_plant_coh.png]] - - -Then, the transfer function from the DAC output voltage $V_a$ to the measured displacement by the encoders is computed: -#+begin_src matlab -%% Transfer function estimation +%% FRF estimation of the transfer function from u to de enc_frf = zeros(length(f), length(apa_nums)); for i = 1:length(apa_nums) - [frf_lf, ~] = tfestimate(apa_sweep{i}.Va, apa_sweep{i}.de, win, [], [], 1/Ts); - [frf_hf, ~] = tfestimate(apa_noise_hf{i}.Va, apa_noise_hf{i}.de, win, [], [], 1/Ts); + [frf_lf, ~] = tfestimate(apa_sweep{i}.u, apa_sweep{i}.de, win, Noverlap, Nfft, 1/Ts); + [frf_hf, ~] = tfestimate(apa_noise_hf{i}.u, apa_noise_hf{i}.de, win, Noverlap, Nfft, 1/Ts); enc_frf(:, i) = [frf_lf(i_lf); frf_hf(i_hf)]; end + +%% FRF estimation of the transfer function from u to Vs +iff_frf = zeros(length(f), length(apa_nums)); +for i = 1:length(apa_nums) + [frf_lf, ~] = tfestimate(apa_sweep{i}.u, apa_sweep{i}.Vs, win, Noverlap, Nfft, 1/Ts); + [frf_hf, ~] = tfestimate(apa_noise_hf{i}.u, apa_noise_hf{i}.Vs, win, Noverlap, Nfft, 1/Ts); + iff_frf(:, i) = [frf_lf(i_lf); frf_hf(i_hf)]; +end #+end_src -The obtained transfer functions are shown in Figure ref:fig:apa_frf_dvf_plant_tf. -They are all superimposed. +#+begin_src matlab :tangle no :exports none +%% Save the identified dynamics for further analysis +save('matlab/mat/meas_apa_frf.mat', 'f', 'Ts', 'enc_frf', 'iff_frf', 'apa_nums'); +#+end_src + +#+begin_src matlab :eval no +%% Save the identified dynamics for further analysis +save('mat/meas_apa_frf.mat', 'f', 'Ts', 'enc_frf', 'iff_frf', 'apa_nums'); +#+end_src + +The obtained transfer functions for the 6 APA between the excitation voltage $u$ and the encoder displacement $d_e$ are shown in Figure ref:fig:test_apa_frf_encoder. +The obtained transfer functions are close to a mass-spring-damper system. +The following can be observed: +- A "stiffness line" indicating a static gain equal to $\approx -17\,\mu m/V$. + The minus sign comes from the fact that an increase in voltage stretches the piezoelectric stack that then reduces the height of the APA +- A lightly damped resonance at $95\,\text{Hz}$ +- A "mass line" up to $\approx 800\,\text{Hz}$, above which some resonances appear #+begin_src matlab :exports none +%% Plot the FRF from u to de figure; -tiledlayout(3, 1, 'TileSpacing', 'None', 'Padding', 'None'); +tiledlayout(3, 1, 'TileSpacing', 'Compact', 'Padding', 'None'); ax1 = nexttile([2,1]); hold on; @@ -2284,10 +933,10 @@ for i = 1:length(apa_nums) end hold off; set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); -ylabel('Amplitude $d_e/V_a$ [m/V]'); set(gca, 'XTickLabel',[]); +ylabel('Amplitude $d_e/u$ [m/V]'); set(gca, 'XTickLabel',[]); hold off; legend('location', 'northeast', 'FontSize', 8, 'NumColumns', 2); -ylim([1e-9, 1e-3]); +ylim([1e-8, 1e-3]); ax2 = nexttile; hold on; @@ -2305,121 +954,32 @@ xlim([10, 2e3]); #+end_src #+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_frf_dvf_plant_tf.pdf', 'width', 'wide', 'height', 'tall'); +exportFig('figs/test_apa_frf_encoder.pdf', 'width', 'wide', 'height', 'tall'); #+end_src -#+name: fig:apa_frf_dvf_plant_tf -#+caption: Estimated FRF for the DVF plant (transfer function from $V_a$ to the encoder $d_e$) +#+name: fig:test_apa_frf_encoder +#+caption: Estimated Frequency Response Function from generated voltage $u$ to the encoder displacement $d_e$ for the 6 APA300ML #+RESULTS: -[[file:figs/apa_frf_dvf_plant_tf.png]] +[[file:figs/test_apa_frf_encoder.png]] -A zoom on the main resonance is shown in Figure ref:fig:apa_frf_dvf_zoom_res_plant_tf. -It is clear that the responses around the resonances are well matching for all the APA. +The dynamics from $u$ to the measured voltage across the sensor stack $V_s$ is also identified and shown in Figure ref:fig:test_apa_frf_force. -It is also clear that there is not a single resonance but two resonances, a first one at 95Hz and a second one at 105Hz. +A lightly damped resonance is observed at $95\,\text{Hz}$ and a lightly damped anti-resonance at $41\,\text{Hz}$. +No additional resonances is present up to at least $2\,\text{kHz}$ indicating at Integral Force Feedback can be applied without stability issues from high frequency flexible modes. -#+begin_question -Why is there a double resonance at around 94Hz? -#+end_question +As illustrated by the Root Locus, the poles of the closed-loop system converges to the zeros of the open-loop plant. +Suppose that a controller with a very high gain is implemented such that the voltage $V_s$ across the sensor stack is zero. +In that case, because of the very high controller gain, no stress and strain is present on the sensor stack (and on the actuator stacks are well, as they are both in series). +Such closed-loop system would therefore virtually corresponds to a system for which the piezoelectric stacks have been removed and just the mechanical shell is kept. +From this analysis, the axial stiffness of the shell can be estimated to be $k_{\text{shell}} = 5.7 \cdot (2\pi \cdot 41)^2 = 0.38\,N/\mu m$. +# TODO - Compare with FEM result + +Such reasoning can lead to very interesting insight into the system just from an open-loop identification. #+begin_src matlab :exports none +%% Plot the FRF from u to Vs figure; -tiledlayout(3, 1, 'TileSpacing', 'None', 'Padding', 'None'); - -ax1 = nexttile([2,1]); -hold on; -for i = 1:length(apa_nums) - plot(f, abs(enc_frf(:, i)), ... - 'DisplayName', sprintf('APA %i', apa_nums(i))); -end -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); -ylabel('Amplitude $d_e/V_a$ [m/V]'); set(gca, 'XTickLabel',[]); -hold off; -legend('location', 'northeast', 'FontSize', 8, 'NumColumns', 2); -ylim([2e-5, 4e-4]); - -ax2 = nexttile; -hold on; -for i = 1:length(apa_nums) - plot(f, 180/pi*angle(enc_frf(:, i))); -end -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); -xlabel('Frequency [Hz]'); ylabel('Phase [deg]'); -hold off; -yticks(-360:90:360); -ylim([-10, 180]); - -linkaxes([ax1,ax2],'x'); -xlim([80, 120]); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_frf_dvf_zoom_res_plant_tf.pdf', 'width', 'wide', 'height', 'tall'); -#+end_src - -#+name: fig:apa_frf_dvf_zoom_res_plant_tf -#+caption: Estimated FRF for the DVF plant (transfer function from $V_a$ to the encoder $d_e$) - Zoom on the main resonance -#+RESULTS: -[[file:figs/apa_frf_dvf_zoom_res_plant_tf.png]] - -*** FRF - Force Sensor -In this section, the dynamics from $V_a$ to $V_s$ is identified. - -First the coherence is computed and shown in Figure ref:fig:apa_frf_iff_plant_coh. -The coherence is very nice from 10Hz to 2kHz. -It is only dropping near a zeros at 40Hz, and near the resonance at 95Hz (the excitation amplitude being lowered). - -#+begin_src matlab -%% Compute the Coherence -coh_iff = zeros(length(f), length(apa_nums)); -for i = 1:length(apa_nums) - [coh_lf, ~] = mscohere(apa_sweep{i}.Va, apa_sweep{i}.Vs, win, [], [], 1/Ts); - [coh_hf, ~] = mscohere(apa_noise_hf{i}.Va, apa_noise_hf{i}.Vs, win, [], [], 1/Ts); - coh_iff(:, i) = [coh_lf(i_lf); coh_hf(i_hf)]; -end -#+end_src - -#+begin_src matlab :exports none -%% Plot the coherence -figure; -hold on; -for i = 1:length(apa_nums) - plot(f, coh_iff(:, i), ... - 'DisplayName', sprintf('APA %i', apa_nums(i))); -end; -hold off; -xlabel('Frequency [Hz]'); ylabel('Coherence [-]'); -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); -xlim([5, 5e3]); ylim([0, 1]); -legend('location', 'southwest', 'FontSize', 8, 'NumColumns', 2); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_frf_iff_plant_coh.pdf', 'width', 'wide', 'height', 'normal'); -#+end_src - -#+name: fig:apa_frf_iff_plant_coh -#+caption: Obtained coherence for the IFF plant -#+RESULTS: -[[file:figs/apa_frf_iff_plant_coh.png]] - -Then the FRF are estimated and shown in Figure ref:fig:apa_frf_iff_plant_tf -#+begin_src matlab -%% FRF estimation of the transfer function from Va to Vs -iff_frf = zeros(length(f), length(apa_nums)); -for i = 1:length(apa_nums) - [frf_lf, ~] = tfestimate(apa_sweep{i}.Va, apa_sweep{i}.Vs, win, [], [], 1/Ts); - [frf_hf, ~] = tfestimate(apa_noise_hf{i}.Va, apa_noise_hf{i}.Vs, win, [], [], 1/Ts); - iff_frf(:, i) = [frf_lf(i_lf); frf_hf(i_hf)]; -end -#+end_src - -#+begin_src matlab :exports none -%% Plot the FRF from Va to Vs -figure; -tiledlayout(2, 1, 'TileSpacing', 'None', 'Padding', 'None'); +tiledlayout(2, 1, 'TileSpacing', 'Compact', 'Padding', 'None'); ax1 = nexttile; hold on; @@ -2429,7 +989,7 @@ for i = 1:length(apa_nums) end hold off; set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); -ylabel('Amplitude $V_s/V_a$ [V/V]'); set(gca, 'XTickLabel',[]); +ylabel('Amplitude $V_s/u$ [V/V]'); set(gca, 'XTickLabel',[]); hold off; ylim([1e-2, 1e2]); legend('location', 'southeast', 'FontSize', 8, 'NumColumns', 2); @@ -2450,45 +1010,352 @@ xlim([10, 2e3]); #+end_src #+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_frf_iff_plant_tf.pdf', 'width', 'wide', 'height', 'tall'); +exportFig('figs/test_apa_frf_force.pdf', 'width', 'wide', 'height', 'tall'); #+end_src -#+name: fig:apa_frf_iff_plant_tf -#+caption:Identified IFF Plant +#+name: fig:test_apa_frf_force +#+caption: Estimated Frequency Response Function from generated voltage $u$ to the sensor stack voltage $V_s$ for the 6 APA300ML #+RESULTS: -[[file:figs/apa_frf_iff_plant_tf.png]] +[[file:figs/test_apa_frf_force.png]] -*** Conclusion +All the identified dynamics of the six APA300ML (both when looking at the encoder in Figure ref:fig:test_apa_frf_encoder and at the force sensor in Figure ref:fig:test_apa_frf_force) are almost identical, indicating good manufacturing repeatability for the piezoelectric stacks and the mechanical lever. + +** Effect of the resistor on the IFF Plant +<> + +A resistor $R \approx 80.6\,k\Omega$ is added in parallel with the sensor stack which has the effect to form a high pass filter with the capacitance of the stack. + +As explain before, this is done for two reasons: +1. Limit the voltage offset due to the input bias current of the ADC +2. Limit the low frequency gain + +The (low frequency) transfer function from $u$ to $V_s$ with and without this resistor have been measured and are compared in Figure ref:fig:test_apa_effect_resistance. +It is confirmed that the added resistor as the effect of adding an high pass filter with a cut-off frequency of $\approx 0.35\,\text{Hz}$. + +#+begin_src matlab +%% Load the data +wi_k = load('frf_data_1_sweep_lf_with_R.mat', 't', 'Vs', 'Va'); % With the resistor +wo_k = load('frf_data_1_sweep_lf.mat', 't', 'Vs', 'Va'); % Without the resistor + +%% Large Hanning window for good low frequency estimate +Nfft = floor(50/Ts); +win = hanning(Nfft); +Noverlap = floor(Nfft/2); + +%% Compute the transfer functions from Va to Vs +[frf_wo_k, f] = tfestimate(wo_k.Va, wo_k.Vs, win, Noverlap, Nfft, 1/Ts); +[frf_wi_k, ~] = tfestimate(wi_k.Va, wi_k.Vs, win, Noverlap, Nfft, 1/Ts); + +%% Model for the high pass filter +C = 5.1e-6; % Sensor Stack capacitance [F] +R = 80.6e3; % Parallel Resistor [Ohm] + +f0 = 1/(2*pi*R*C); % Crossover frequency of RC HPF [Hz] + +G_hpf = 0.6*(s/2*pi*f0)/(1 + s/2*pi*f0); +#+end_src + +#+begin_src matlab :exports none +%% Compare the HPF model and the measured FRF +figure; +tiledlayout(3, 1, 'TileSpacing', 'Compact', 'Padding', 'None'); + +ax1 = nexttile([2,1]); +hold on; +plot(f, abs(frf_wo_k), 'DisplayName', 'Without $R$'); +plot(f, abs(frf_wi_k), 'DisplayName', 'With $R$'); +hold off; +set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); +ylabel('Amplitude $V_s/u$ [V/V]'); set(gca, 'XTickLabel',[]); +hold off; +ylim([1e-1, 1e0]); +legend('location', 'southeast') + +ax2 = nexttile; +hold on; +plot(f, 180/pi*angle(frf_wo_k)); +plot(f, 180/pi*angle(frf_wi_k)); +hold off; +set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); +xlabel('Frequency [Hz]'); ylabel('Phase [deg]'); +hold off; +yticks(-360:45:360); ylim([-45, 90]); + +linkaxes([ax1,ax2],'x'); +xlim([0.2, 8]); +#+end_src + +#+begin_src matlab :tangle no :exports results :results file replace +exportFig('figs/test_apa_effect_resistance.pdf', 'width', 'wide', 'height', 'tall'); +#+end_src + +#+name: fig:test_apa_effect_resistance +#+caption: Transfer function from u to $V_s$ with and without the resistor $R$ in parallel with the piezoelectric stack used as the force sensor +#+RESULTS: +[[file:figs/test_apa_effect_resistance.png]] + +** Integral Force Feedback +<> + +This test bench can also be used to estimate the damping added by the implementation of an Integral Force Feedback strategy. + +#+begin_src matlab +%% Load identification Data +data = load("2023-03-17_11-28_iff_plant.mat"); + +%% Spectral Analysis setup +Ts = 1e-4; % Sampling Time [s] +Nfft = floor(5/Ts); +win = hanning(Nfft); +Noverlap = floor(Nfft/2); + +%% Compute the transfer function from applied force to measured rotation +[G_iff, f] = tfestimate(data.id_plant, data.Vs, win, Noverlap, Nfft, 1/Ts); +#+end_src + +First, the transfer function eqref:eq:test_apa_iff_manual_fit is manually tuned to match the identified dynamics from generated voltage $u$ to the measured sensor stack voltage $V_s$ in Section ref:ssec:test_apa_meas_dynamics. + +The obtained parameter values are $\omega_{\textsc{hpf}} = 0.4\, \text{Hz}$, $\omega_{z} = 42.7\, \text{Hz}$, $\xi_{z} = 0.4\,\%$, $\omega_{p} = 95.2\, \text{Hz}$, $\xi_{p} = 2\,\%$ and $g_0 = 0.64$. + +\begin{equation} \label{eq:test_apa_iff_manual_fit} +G_{\textsc{iff},m}(s) = g_0 \cdot \frac{1 + 2 \xi_z \frac{s}{\omega_z} + \frac{s^2}{\omega_z^2}}{1 + 2 \xi_p \frac{s}{\omega_p} + \frac{s^2}{\omega_p^2}} \cdot \frac{s}{\omega_{\textsc{hpf}} + s} +\end{equation} + +The comparison between the identified plant and the manually tuned transfer function is done in Figure ref:fig:test_apa_iff_plant_comp_manual_fit. + +#+begin_src matlab +%% Basic manually tuned model +w0z = 2*pi*42.7; % Zero frequency +xiz = 0.004; % Zero damping + +w0p = 2*pi*95.2; % Pole frequency +xip = 0.02; % Pole damping + +G_iff_model = exp(-2*s*Ts)*0.64*(1 + 2*xiz/w0z*s + s^2/w0z^2)/(1 + 2*xip/w0p*s + s^2/w0p^2)*(s/(s+2*pi*0.4)); +#+end_src + +#+begin_src matlab :exports none :results none +%% Identified IFF plant and manually tuned model of the plant +figure; +tiledlayout(3, 1, 'TileSpacing', 'Compact', 'Padding', 'None'); + +ax1 = nexttile([2,1]); +hold on; +plot(f, abs(G_iff), 'color', colors(2,:), 'DisplayName', 'Identified plant') +plot(f, abs(squeeze(freqresp(G_iff_model, f, 'Hz'))), 'k--', 'DisplayName', 'Manual fit') +hold off; +set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); +ylabel('Amplitude $V_s/u$ [V/V]'); set(gca, 'XTickLabel',[]); +legend('location', 'southeast', 'FontSize', 8, 'NumColumns', 1); + +ax2 = nexttile; +hold on; +plot(f, 180/pi*angle(G_iff), 'color', colors(2,:)); +plot(f, 180/pi*angle(squeeze(freqresp(G_iff_model, f, 'Hz'))), 'k--') +hold off; +set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); +xlabel('Frequency [Hz]'); ylabel('Phase [deg]'); +hold off; +yticks(-360:45:360); +ylim([-90, 180]) + +linkaxes([ax1,ax2],'x'); +xlim([0.2, 1e3]); +#+end_src + +#+begin_src matlab :tangle no :exports results :results file replace +exportFig('figs/test_apa_iff_plant_comp_manual_fit.pdf', 'width', 'wide', 'height', 'tall'); +#+end_src + +#+name: fig:test_apa_iff_plant_comp_manual_fit +#+caption: Identified IFF plant and manually tuned model of the plant (a time delay of $200\,\mu s$ is added to the model of the plant to better match the identified phase) +#+RESULTS: +[[file:figs/test_apa_iff_plant_comp_manual_fit.png]] + +The implemented Integral Force Feedback Controller transfer function is shown in equation eqref:eq:test_apa_Kiff_formula. +It contains an high pass filter (cut-off frequency of $2\,\text{Hz}$) to limit the low frequency gain, a low pass filter to add integral action above $20\,\text{Hz}$, a second low pass filter to add robustness to high frequency resonances and a tunable gain $g$. + +\begin{equation} \label{eq:test_apa_Kiff_formula} +K_{\textsc{iff}}(s) = -10 \cdot g \cdot \frac{s}{s + 2\pi \cdot 2} \cdot \frac{1}{1 + 2\pi \cdot 20} \cdot \frac{1}{s + 2\pi\cdot 2000} +\end{equation} + +#+begin_src matlab +%% Integral Force Feedback Controller +K_iff = -10*(1/(s + 2*pi*20)) * ... % LPF: provides integral action above 20Hz + (s/(s + 2*pi*2)) * ... % HPF: limit low frequency gain + (1/(1 + s/2/pi/2e3)); % LPF: more robust to high frequency resonances +#+end_src + +To estimate how the dynamics of the APA changes when the Integral Force Feedback controller is implemented, the test bench shown in Figure ref:fig:test_apa_iff_schematic is used. +The transfer function from the "damped" plant input $u\prime$ to the encoder displacement $d_e$ is identified for several IFF controller gains $g$. + +#+name: fig:test_apa_iff_schematic +#+caption: Figure caption +[[file:figs/test_apa_iff_schematic.png]] + +#+begin_src matlab +%% Load Data +data = load("2023-03-17_14-10_damped_plants_new.mat"); + +%% Spectral Analysis setup +Ts = 1e-4; % Sampling Time [s] +Nfft = floor(1/Ts); +win = hanning(Nfft); +Noverlap = floor(Nfft/2); + +%% Get the frequency vector +[~, f] = tfestimate(data.data(1).id_plant(1:end), data.data(1).dL(1:end), win, Noverlap, Nfft, 1/Ts); + +%% Gains used for analysis are between 1 and 50 +i_kept = [5:10] + +%% Identify the damped plant from u' to de for different IFF gains +G_dL_frf = {zeros(1,length(i_kept))}; + +for i = 1:length(i_kept) + [G_dL, ~] = tfestimate(data.data(i_kept(i)).id_plant(1:end), data.data(i_kept(i)).dL(1:end), win, Noverlap, Nfft, 1/Ts); + G_dL_frf(i) = {G_dL}; +end +#+end_src + +The identified dynamics are then fitted by second order transfer functions using the "Vector Fitting" toolbox [[cite:&gustavsen99_ration_approx_frequen_domain_respon]]. +The comparison between the identified damped dynamics and the fitted second order transfer functions is done in Figure ref:fig:test_apa_identified_damped_plants for different gains $g$. +It is clear that large amount of damping is added when the gain is increased and that the frequency of the pole is shifted to lower frequencies. + +#+begin_src matlab +%% Fit the data with 2nd order transfer function using vectfit3 +opts = struct(); + +opts.stable = 1; % Enforce stable poles +opts.asymp = 1; % Force D matrix to be null +opts.relax = 1; % Use vector fitting with relaxed non-triviality constraint +opts.skip_pole = 0; % Do NOT skip pole identification +opts.skip_res = 0; % Do NOT skip identification of residues (C,D,E) +opts.cmplx_ss = 0; % Create real state space model with block diagonal A + +opts.spy1 = 0; % No plotting for first stage of vector fitting +opts.spy2 = 0; % Create magnitude plot for fitting of f(s) + + +Niter = 100; % Number of iteration. +N = 2; % Order of approximation +poles = [-25 - 1i*60, -25 + 1i*60]; % First get for the pole location + +G_dL_id = {zeros(1,length(i_kept))}; + +% Identification just between two frequencies +f_keep = (f>20 & f<200); + +for i = 1:length(i_kept) + %% Estimate resonance frequency and damping + for iter = 1:Niter + [G_est, poles, ~, frf_est] = vectfit3(G_dL_frf{i}(f_keep).', 1i*2*pi*f(f_keep)', poles, ones(size(f(f_keep)))', opts); + end + G_dL_id(i) = {ss(G_est.A, G_est.B, G_est.C, G_est.D)}; +end +#+end_src + +#+begin_src matlab :exports none :results none +%% Identified dynamics from u' to de for different IFF gains +figure; +tiledlayout(1, 1, 'TileSpacing', 'Compact', 'Padding', 'None'); + +ax1 = nexttile(); +hold on; +for i = 1:length(i_kept) + plot(f, abs(G_dL_frf{i}), 'color', [colors(i,:), 1], 'DisplayName', sprintf('g = %.0f', data.gains(i_kept(i)))) + plot(f, abs(squeeze(freqresp(G_dL_id{i}, f, 'Hz'))), '--', 'color', [colors(i,:), 1], 'HandleVisibility', 'off') +end +hold off; +set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); +xlabel('Frequency [Hz]'); ylabel('Amplitude $d_L/V_a$ [m/V]'); +xlim([10, 1e3]); +legend('location', 'northeast', 'FontSize', 8, 'NumColumns', 1); +#+end_src + +#+begin_src matlab :tangle no :exports results :results file replace +exportFig('figs/test_apa_identified_damped_plants.pdf', 'width', 'wide', 'height', 'normal'); +#+end_src + +#+name: fig:test_apa_identified_damped_plants +#+caption: Identified dynamics (solid lines) and fitted transfer functions (dashed lines) from $u\prime$ to $d_e$ for different IFF gains +#+RESULTS: +[[file:figs/test_apa_identified_damped_plants.png]] + +The evolution of the pole in the complex plane as a function of the controller gain $g$ (i.e. the "root locus") is computed: +- using the IFF plant model eqref:eq:test_apa_iff_manual_fit and the implemented controller eqref:eq:test_apa_Kiff_formula +- from the fitted transfer functions of the damped plants experimentally identified for several controller gains + +The two obtained root loci are compared in Figure ref:fig:test_apa_iff_root_locus and are in good agreement considering that the damped plants were only fitted using a second order transfer function. + +#+begin_src matlab :exports none :results none +%% Root Locus of the APA300ML with Integral Force Feedback +% Comparison between the computed root locus from the plant model and the root locus estimated from the damped plant pole identification +figure; +gains = logspace(-1, 3, 1000); + +figure; +hold on; +G_iff_poles = pole(G_iff_model); +i = imag(G_iff_poles) > 100; % Only keep relevant poles +plot(real(G_iff_poles(i)), imag(G_iff_poles(i)), 'kx', ... + 'DisplayName', '$g = 0$'); +G_iff_zeros = tzero(G_iff_model); +i = imag(G_iff_zeros) > 100; % Only keep relevant zeros +plot(real(G_iff_zeros(i)), imag(G_iff_zeros(i)), 'ko', ... + 'HandleVisibility', 'off'); + +for g = gains + clpoles = pole(feedback(G_iff_model, g*K_iff, 1)); + i = imag(clpoles) > 100; % Only keep relevant poles + plot(real(clpoles(i)), imag(clpoles(i)), 'k.', ... + 'HandleVisibility', 'off'); +end + +for i = 1:length(i_kept) + plot(real(pole(G_dL_id{i})), imag(pole(G_dL_id{i})), 'x', 'color', [colors(i,:), 1], 'DisplayName', sprintf('g = %1.f', data.gains(i_kept(i)))); +end +ylim([0, 700]); +xlim([-600,100]); +xlabel('Real Part') +ylabel('Imaginary Part') +axis square +legend('location', 'northwest'); +#+end_src + +#+begin_src matlab :tangle no :exports results :results file replace +exportFig('figs/test_apa_iff_root_locus.pdf', 'width', 'wide', 'height', 'tall'); +#+end_src + +#+name: fig:test_apa_iff_root_locus +#+caption: Root Locus of the APA300ML with Integral Force Feedback - Comparison between the computed root locus from the plant model (black line) and the root locus estimated from the damped plant pole identification (colorful crosses) +#+RESULTS: +[[file:figs/test_apa_iff_root_locus.png]] +** Conclusion #+begin_important So far, all the measured FRF are showing the dynamical behavior that was expected. #+end_important -#+begin_src matlab :tangle no :exports none -save('matlab/mat/meas_apa_frf.mat', 'f', 'Ts', 'enc_frf', 'iff_frf', 'apa_nums'); -#+end_src -#+begin_src matlab :eval no -%% Save the measured FRF -save('mat/meas_apa_frf.mat', 'f', 'Ts', 'enc_frf', 'iff_frf', 'apa_nums'); -#+end_src - -* Test Bench APA300ML - Simscape Model +* TODO Test Bench APA300ML - Simscape Model :PROPERTIES: -:header-args:matlab+: :tangle matlab/apa_simscape_model_comp.m +:header-args:matlab+: :tangle matlab/3_test_apa_simscape.m :END: -<> +<> ** Introduction :ignore: -In this section, a simscape model (Figure ref:fig:model_bench_apa) of the measurement bench is used to compare the model of the APA with the measured FRF. +In this section, a simscape model (Figure ref:fig:test_apa_bench_model) of the measurement bench is used to compare the model of the APA with the measured FRF. After the transfer functions are extracted from the model (Section ref:sec:simscape_bench_apa_first_id), the comparison of the obtained dynamics with the measured FRF will permit to: 1. Estimate the "actuator constant" and "sensor constant" (Section ref:sec:simscape_bench_apa_id_constants) +- "Actuator constant": Gain from the applied voltage $V_a$ to the generated Force $F_a$ +- "Sensor constant": Gain from the sensor stack strain $\delta L$ to the generated voltage $V_s$ 2. Tune the model of the APA to match the measured dynamics (Section ref:sec:simscape_bench_apa_tune_2dof_model) -#+name: fig:model_bench_apa +#+name: fig:test_apa_bench_model #+caption: Screenshot of the Simscape model #+attr_latex: :width 0.5\linewidth -[[file:figs/model_bench_apa.png]] +[[file:figs/test_apa_bench_model.png]] ** Matlab Init :noexport:ignore: #+begin_src matlab :tangle no :exports none :results silent :noweb yes :var current_dir=(file-name-directory buffer-file-name) @@ -2502,16 +1369,14 @@ After the transfer functions are extracted from the model (Section ref:sec:simsc #+begin_src matlab :tangle no %% Add useful folders to the path addpath('matlab/'); -addpath('matlab/test_bench_apa300ml/'); +addpath('matlab/STEPS/'); addpath('matlab/mat/'); addpath('matlab/src/'); -addpath('matlab/png/'); #+end_src #+begin_src matlab :eval no %% Add useful folders to the path -addpath('test_bench_apa300ml/'); -addpath('png/'); +addpath('STEPS/'); addpath('mat/'); addpath('src/'); #+end_src @@ -2527,7 +1392,7 @@ options = linearizeOptions; options.SampleTime = 0; % Name of the Simulink File -mdl = 'test_bench_apa300ml'; +mdl = 'test_apa300ml'; open(mdl) #+end_src @@ -2548,14 +1413,13 @@ n_hexapod.actuator = initializeAPA(... The transfer function from excitation voltage $V_a$ (before the amplification of $20$ due to the PD200 amplifier) to: 1. the sensor stack voltage $V_s$ 2. the measured displacement by the encoder $d_e$ -3. the measured displacement by the interferometer $d_a$ + #+begin_src matlab %% Input/Output definition clear io; io_i = 1; io(io_i) = linio([mdl, '/Va'], 1, 'openinput'); io_i = io_i + 1; % DAC Voltage io(io_i) = linio([mdl, '/Vs'], 1, 'openoutput'); io_i = io_i + 1; % Sensor Voltage io(io_i) = linio([mdl, '/de'], 1, 'openoutput'); io_i = io_i + 1; % Encoder -io(io_i) = linio([mdl, '/da'], 1, 'openoutput'); io_i = io_i + 1; % Interferometer %% Run the linearization Ga = linearize(mdl, io, 0.0, options); @@ -2576,7 +1440,7 @@ It can be seen that: freqs = logspace(1, 3, 1000); figure; -tiledlayout(3, 1, 'TileSpacing', 'None', 'Padding', 'None'); +tiledlayout(3, 1, 'TileSpacing', 'Compact', 'Padding', 'None'); ax1 = nexttile([2,1]); hold on; @@ -2613,12 +1477,11 @@ exportFig('figs/apa_model_bench_bode_vs.pdf', 'width', 'wide', 'height', 'normal freqs = logspace(1, 3, 1000); figure; -tiledlayout(3, 1, 'TileSpacing', 'None', 'Padding', 'None'); +tiledlayout(3, 1, 'TileSpacing', 'Compact', 'Padding', 'None'); ax1 = nexttile([2,1]); hold on; plot(freqs, abs(squeeze(freqresp(Ga('de', 'Va'), freqs, 'Hz'))), 'DisplayName', 'Encoder') -plot(freqs, abs(squeeze(freqresp(Ga('da', 'Va'), freqs, 'Hz'))), 'DisplayName', 'Interferometer') hold off; set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); ylabel('Amplitude $d/V_a$ [m/V]'); set(gca, 'XTickLabel',[]); @@ -2628,7 +1491,6 @@ legend('location', 'southwest'); ax2 = nexttile; hold on; plot(freqs, 180/pi*angle(squeeze(freqresp(Ga('de', 'Va'), freqs, 'Hz')))) -plot(freqs, 180/pi*angle(squeeze(freqresp(Ga('da', 'Va'), freqs, 'Hz')))) set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); xlabel('Frequency [Hz]'); ylabel('Phase [deg]'); hold off; @@ -2777,7 +1639,7 @@ The transfer functions from $V_a$ to $d_e$ are compared in Figure ref:fig:apa_ac freqs = logspace(1,4,1000); figure; -tiledlayout(3, 1, 'TileSpacing', 'None', 'Padding', 'None'); +tiledlayout(3, 1, 'TileSpacing', 'Compact', 'Padding', 'None'); ax1 = nexttile([2,1]); hold on; @@ -2823,7 +1685,7 @@ exportFig('figs/apa_act_constant_comp.pdf', 'width', 'wide', 'height', 'tall'); freqs = logspace(1,4,1000); figure; -tiledlayout(3, 1, 'TileSpacing', 'None', 'Padding', 'None'); +tiledlayout(3, 1, 'TileSpacing', 'Compact', 'Padding', 'None'); ax1 = nexttile([2,1]); hold on; @@ -3026,7 +1888,7 @@ The obtained dynamics is compared with the measured one in Figures ref:fig:apa_a #+begin_src matlab :exports none %% Bode plot of the transfer function from V_a to d_e (both Simscape and measured FRF) figure; -tiledlayout(3, 1, 'TileSpacing', 'None', 'Padding', 'None'); +tiledlayout(3, 1, 'TileSpacing', 'Compact', 'Padding', 'None'); ax1 = nexttile([2,1]); hold on; @@ -3070,7 +1932,7 @@ exportFig('figs/apa_act_constant_comp_flex.pdf', 'width', 'wide', 'height', 'tal #+begin_src matlab :exports none %% Bode plot of the transfer function from Va to Vs (both Simscape and measured FRF) figure; -tiledlayout(3, 1, 'TileSpacing', 'None', 'Padding', 'None'); +tiledlayout(3, 1, 'TileSpacing', 'Compact', 'Padding', 'None'); ax1 = nexttile([2,1]); hold on; @@ -3152,7 +2014,7 @@ The dynamics is identified using the Simscape model and compared with the measur %% Comparison of the experimental data and Simscape Model freqs = 5*logspace(0, 3, 1000); figure; -tiledlayout(3, 2, 'TileSpacing', 'None', 'Padding', 'None'); +tiledlayout(3, 2, 'TileSpacing', 'Compact', 'Padding', 'None'); ax1 = nexttile([2,1]); hold on; @@ -3223,213 +2085,929 @@ exportFig('figs/comp_apa_plant_after_opt.pdf', 'width', 'full', 'height', 'tall' The tuned 2DoF is very well representing the (axial) dynamics of the APA. #+end_important -** For Philipp and my papers (MEDSI) :noexport: +* TODO Compare with the FEM/Simscape Model :noexport: +** Introduction :ignore: +In this section, the Amplified Piezoelectric Actuator APA300ML ([[file:doc/APA300ML.pdf][doc]]) is modeled using a Finite Element Software. +Then a /super element/ is exported and imported in Simscape where its dynamic is studied. -#+begin_src matlab -%% Optimized parameters -n_hexapod.actuator = initializeAPA('type', '2dof', ... - 'Ga', -32.2, ... - 'Gs', 0.088, ... - 'k', ones(6,1)*0.38e6, ... - 'ke', ones(6,1)*1.75e6, ... - 'ka', ones(6,1)*3e7, ... - 'c', ones(6,1)*5e0, ... - 'ce', ones(6,1)*9e1, ... - 'ca', ones(6,1)*9e1 ... - ); +A 3D view of the Amplified Piezoelectric Actuator (APA300ML) is shown in Figure ref:fig:test_apa_ansys. +The remote point used are also shown in this figure. + +#+name: fig:test_apa_ansys +#+caption: Ansys FEM of the APA300ML +[[file:figs/test_apa_ansys.jpg]] + +** Matlab Init :noexport:ignore: +#+begin_src matlab :tangle no :exports none :results silent :noweb yes :var current_dir=(file-name-directory buffer-file-name) + <> #+end_src -#+begin_src matlab :exports none -%% Input/Output definition -clear io; io_i = 1; -io(io_i) = linio([mdl, '/Va'], 1, 'openinput'); io_i = io_i + 1; % Actuator Voltage -io(io_i) = linio([mdl, '/Vs'], 1, 'openoutput'); io_i = io_i + 1; % Sensor Voltage -io(io_i) = linio([mdl, '/de'], 1, 'openoutput'); io_i = io_i + 1; % Encoder - -%% Identification with optimized parameters -Gs = exp(-s*Ts)*linearize(mdl, io, 0.0, options); -Gs.InputName = {'Va'}; -Gs.OutputName = {'Vs', 'de'}; +#+begin_src matlab :exports none :results silent :noweb yes + <> #+end_src -#+begin_src matlab :exports none -%% Comparison of the experimental data and Simscape Model -freqs = 5*logspace(0, 3, 1000); - -figure; -tiledlayout(3, 2, 'TileSpacing', 'None', 'Padding', 'None'); - -ax1 = nexttile([2,1]); -hold on; -plot(f, abs(iff_frf(:, 1)), '-'); -plot(freqs, abs(squeeze(freqresp(Gs('Vs', 'Va'), freqs, 'Hz'))), '--'); -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); -ylabel('Amplitude $V_s/V_a$ [-]'); set(gca, 'XTickLabel',[]); -hold off; -ylim([1e-2, 1e2]); - -ax1b = nexttile([2,1]); -hold on; -plot(f, abs(enc_frf(:, 1)), ... - 'DisplayName', 'Meas. FRF'); -plot(freqs, abs(squeeze(freqresp(Gs('de', 'Va'), freqs, 'Hz'))), '--', ... - 'DisplayName', 'Simscape'); -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); -ylabel('Amplitude $d_e/V_a$ [m/V]'); set(gca, 'XTickLabel',[]); -hold off; -ylim([2e-8, 5e-4]); -legend('location', 'southwest', 'FontSize', 8); - -ax2 = nexttile; -hold on; -plot(f, 180/pi*angle(iff_frf(:, 1))); -plot(freqs, 180/pi*unwrap(angle(squeeze(freqresp(Gs('Vs', 'Va'), freqs, 'Hz')))), '--') -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); -xlabel('Frequency [Hz]'); ylabel('Phase [deg]'); -hold off; -yticks(-360:90:360); ylim([-45, 180]); - -ax2b = nexttile; -hold on; -plot(f, 180/pi*angle(enc_frf(:, 1))); -plot(freqs, 180/pi*angle(squeeze(freqresp(Gs('de', 'Va'), freqs, 'Hz'))), '--') -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); -xlabel('Frequency [Hz]'); ylabel('Phase [deg]'); -hold off; -yticks(-360:90:360); ylim([-45, 180]); - -linkaxes([ax1,ax2, ax1b, ax2b],'x'); -xlim([10, 1e3]); +#+begin_src matlab :tangle no + addpath('matlab/'); + addpath('matlab/APA300ML/'); #+end_src -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/apa_test_bench_results.pdf', 'width', 'half', 'height', 'normal'); -#+end_src - -#+name: fig:apa_test_bench_results -#+caption: -#+RESULTS: -[[file:figs/apa_test_bench_results.png]] - - -#+begin_src matlab :exports none -%% Comparison of the experimental data and Simscape Model -freqs = 5*logspace(0, 3, 1000); -figure; -tiledlayout(3, 1, 'TileSpacing', 'None', 'Padding', 'None'); - - -ax2 = nexttile; -hold on; -plot(f, 180/pi*angle(iff_frf(:, 1))); -plot(freqs, 180/pi*unwrap(angle(squeeze(freqresp(Gs('Vs', 'Va'), freqs, 'Hz')))), '--') -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); -xlabel('Frequency [Hz]'); ylabel('Phase [deg]'); -hold off; -yticks(-360:90:360); ylim([-180, 180]); - -linkaxes([ax1,ax2],'x'); -xlim([10, 1e3]); -#+end_src - -#+begin_src matlab :exports none -%% Comparison of the experimental data and Simscape Model -freqs = 5*logspace(0, 3, 1000); -figure; -tiledlayout(3, 1, 'TileSpacing', 'None', 'Padding', 'None'); - -ax1 = nexttile([2,1]); -hold on; -plot(f, abs(enc_frf(:, 1)), ... - 'DisplayName', 'Measured FRF'); -plot(freqs, abs(squeeze(freqresp(Gs('de', 'Va'), freqs, 'Hz'))), '--', ... - 'DisplayName', 'Simscape Model'); -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); -ylabel('Amplitude $d_e/V_a$ [m/V]'); set(gca, 'XTickLabel',[]); -hold off; -ylim([2e-8, 5e-4]); -legend('location', 'southwest'); - -ax2 = nexttile; -hold on; -plot(f, 180/pi*angle(enc_frf(:, 1))); -plot(freqs, 180/pi*angle(squeeze(freqresp(Gs('de', 'Va'), freqs, 'Hz'))), '--') -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); -xlabel('Frequency [Hz]'); ylabel('Phase [deg]'); -hold off; -yticks(-360:90:360); ylim([-90, 180]); - -linkaxes([ax1,ax2],'x'); -xlim([10, 1e3]); -#+end_src - -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/philipp_tf_encoder_comp.pdf', 'width', 'half', 'height', 'normal'); -#+end_src - -#+name: fig:philipp_tf_encoder_comp -#+caption: -#+RESULTS: -[[file:figs/philipp_tf_encoder_comp.png]] - -#+begin_src matlab -%% Load Data -load('meas_apa_frf.mat', 'f', 'Ts', 'enc_frf', 'iff_frf', 'apa_nums'); +#+begin_src matlab :eval no + addpath('APA300ML/'); #+end_src #+begin_src matlab -iff_frf(f<52 & f>10, 1) = conj(iff_frf(f<52 & f>10, 1)); + open('APA300ML.slx'); #+end_src +** Import Mass Matrix, Stiffness Matrix, and Interface Nodes Coordinates +We first extract the stiffness and mass matrices. +#+begin_src matlab + K = readmatrix('APA300ML_mat_K.CSV'); + M = readmatrix('APA300ML_mat_M.CSV'); +#+end_src + +#+begin_src matlab :exports results :results value table replace :tangle no + data2orgtable(K(1:10, 1:10), {}, {}, ' %.1g '); +#+end_src + +#+caption: First 10x10 elements of the Stiffness matrix +#+RESULTS: +| 200000000.0 | 30000.0 | -20000.0 | -70.0 | 300000.0 | 40.0 | 10000000.0 | 10000.0 | -6000.0 | 30.0 | +| 30000.0 | 30000000.0 | 2000.0 | -200000.0 | 60.0 | -10.0 | 4000.0 | 2000000.0 | -500.0 | 9000.0 | +| -20000.0 | 2000.0 | 7000000.0 | -10.0 | -30.0 | 10.0 | 6000.0 | 900.0 | -500000.0 | 3 | +| -70.0 | -200000.0 | -10.0 | 1000.0 | -0.1 | 0.08 | -20.0 | -9000.0 | 3 | -30.0 | +| 300000.0 | 60.0 | -30.0 | -0.1 | 900.0 | 0.1 | 30000.0 | 20.0 | -10.0 | 0.06 | +| 40.0 | -10.0 | 10.0 | 0.08 | 0.1 | 10000.0 | 20.0 | 9 | -5 | 0.03 | +| 10000000.0 | 4000.0 | 6000.0 | -20.0 | 30000.0 | 20.0 | 200000000.0 | 10000.0 | 9000.0 | 50.0 | +| 10000.0 | 2000000.0 | 900.0 | -9000.0 | 20.0 | 9 | 10000.0 | 30000000.0 | -500.0 | 200000.0 | +| -6000.0 | -500.0 | -500000.0 | 3 | -10.0 | -5 | 9000.0 | -500.0 | 7000000.0 | -2 | +| 30.0 | 9000.0 | 3 | -30.0 | 0.06 | 0.03 | 50.0 | 200000.0 | -2 | 1000.0 | + + +#+begin_src matlab :exports results :results value table replace :tangle no + data2orgtable(M(1:10, 1:10), {}, {}, ' %.1g '); +#+end_src + +#+caption: First 10x10 elements of the Mass matrix +#+RESULTS: +| 0.01 | -2e-06 | 1e-06 | 6e-09 | 5e-05 | -5e-09 | -0.0005 | -7e-07 | 6e-07 | -3e-09 | +| -2e-06 | 0.01 | 8e-07 | -2e-05 | -8e-09 | 2e-09 | -9e-07 | -0.0002 | 1e-08 | -9e-07 | +| 1e-06 | 8e-07 | 0.009 | 5e-10 | 1e-09 | -1e-09 | -5e-07 | 3e-08 | 6e-05 | 1e-10 | +| 6e-09 | -2e-05 | 5e-10 | 3e-07 | 2e-11 | -3e-12 | 3e-09 | 9e-07 | -4e-10 | 3e-09 | +| 5e-05 | -8e-09 | 1e-09 | 2e-11 | 6e-07 | -4e-11 | -1e-06 | -2e-09 | 1e-09 | -8e-12 | +| -5e-09 | 2e-09 | -1e-09 | -3e-12 | -4e-11 | 1e-07 | -2e-09 | -1e-09 | -4e-10 | -5e-12 | +| -0.0005 | -9e-07 | -5e-07 | 3e-09 | -1e-06 | -2e-09 | 0.01 | 1e-07 | -3e-07 | -2e-08 | +| -7e-07 | -0.0002 | 3e-08 | 9e-07 | -2e-09 | -1e-09 | 1e-07 | 0.01 | -4e-07 | 2e-05 | +| 6e-07 | 1e-08 | 6e-05 | -4e-10 | 1e-09 | -4e-10 | -3e-07 | -4e-07 | 0.009 | -2e-10 | +| -3e-09 | -9e-07 | 1e-10 | 3e-09 | -8e-12 | -5e-12 | -2e-08 | 2e-05 | -2e-10 | 3e-07 | + + +Then, we extract the coordinates of the interface nodes. +#+begin_src matlab + [int_xyz, int_i, n_xyz, n_i, nodes] = extractNodes('APA300ML_out_nodes_3D.txt'); +#+end_src + +#+begin_src matlab :exports results :results value table replace :tangle no :post addhdr(*this*) + data2orgtable([[1:length(int_i)]', int_i, int_xyz], {}, {'Node i', 'Node Number', 'x [m]', 'y [m]', 'z [m]'}, ' %f '); +#+end_src + +#+caption: Coordinates of the interface nodes +#+RESULTS: +| Node i | Node Number | x [m] | y [m] | z [m] | +|--------+-------------+---------+-------+--------| +| 1.0 | 697783.0 | 0.0 | 0.0 | -0.015 | +| 2.0 | 697784.0 | 0.0 | 0.0 | 0.015 | +| 3.0 | 697785.0 | -0.0325 | 0.0 | 0.0 | +| 4.0 | 697786.0 | -0.0125 | 0.0 | 0.0 | +| 5.0 | 697787.0 | -0.0075 | 0.0 | 0.0 | +| 6.0 | 697788.0 | 0.0125 | 0.0 | 0.0 | +| 7.0 | 697789.0 | 0.0325 | 0.0 | 0.0 | + +#+begin_src matlab :exports results :results value table replace :tangle no + data2orgtable([length(n_i); length(int_i); size(M,1) - 6*length(int_i); size(M,1)], {'Total number of Nodes', 'Number of interface Nodes', 'Number of Modes', 'Size of M and K matrices'}, {}, ' %.0f '); +#+end_src + +#+caption: Some extracted parameters of the FEM +#+RESULTS: +| Total number of Nodes | 7 | +| Number of interface Nodes | 7 | +| Number of Modes | 120 | +| Size of M and K matrices | 162 | + +Using =K=, =M= and =int_xyz=, we can now use the =Reduced Order Flexible Solid= simscape block. + +** Piezoelectric parameters +#+begin_src matlab + Ga = 1; % [N/V] + Gs = 1; % [V/m] +#+end_src + +#+begin_src matlab + m = 0.1; % [kg] +#+end_src + +** Simscape Model +The flexible element is imported using the =Reduced Order Flexible Solid= simscape block. + +Let's say we use two stacks as a force sensor and one stack as an actuator: +- A =Relative Motion Sensor= block is added between the nodes A and C +- An =Internal Force= block is added between the remote points E and B + +The interface nodes are shown in Figure ref:fig:test_apa_ansys. + +One mass is fixed at one end of the piezo-electric stack actuator (remove point F), the other end is fixed to the world frame (remote point G). + +** Identification of the APA Characteristics +*** Stiffness +#+begin_src matlab :exports none + m = 0.0001; +#+end_src + +The transfer function from vertical external force to the relative vertical displacement is identified. + #+begin_src matlab :exports none -%% Comparison of the experimental data and Simscape Model -freqs = 5*logspace(0, 3, 1000); -figure; -tiledlayout(3, 1, 'TileSpacing', 'None', 'Padding', 'None'); + %% Name of the Simulink File + mdl = 'APA300ML'; -ax1 = nexttile([2,1]); -hold on; -plot(f, abs(iff_frf(:, 1)), ... - 'DisplayName', 'Measured FRF'); -plot(freqs, abs(squeeze(freqresp(Gs('Vs', 'Va'), freqs, 'Hz'))), '--', ... - 'DisplayName', 'Simscape Model'); -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); -ylabel('Amplitude $V_s/V_a$ [-]'); set(gca, 'XTickLabel',[]); -hold off; -ylim([1e-2, 1e2]); -legend('location', 'southeast'); + %% Input/Output definition + clear io; io_i = 1; + io(io_i) = linio([mdl, '/Fd'], 1, 'openinput'); io_i = io_i + 1; + io(io_i) = linio([mdl, '/z'], 1, 'openoutput'); io_i = io_i + 1; -ax2 = nexttile; -hold on; -plot(f, 180/pi*angle(iff_frf(:, 1))); -plot(freqs, 180/pi*unwrap(angle(squeeze(freqresp(Gs('Vs', 'Va'), freqs, 'Hz')))), '--') -hold off; -set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); -xlabel('Frequency [Hz]'); ylabel('Phase [deg]'); -hold off; -yticks(-360:90:360); ylim([-180, 180]); - -linkaxes([ax1,ax2],'x'); -xlim([10, 1e3]); + G = linearize(mdl, io); #+end_src -#+begin_src matlab :tangle no :exports results :results file replace -exportFig('figs/philipp_tf_force_sensor_comp.pdf', 'width', 'half', 'height', 'normal'); +The inverse of its DC gain is the axial stiffness of the APA: +#+begin_src matlab :results replace value + 1e-6/dcgain(G) % [N/um] #+end_src #+RESULTS: -[[file:figs/philipp_tf_force_sensor_comp.png]] +: 1.753 + +The specified stiffness in the datasheet is $k = 1.8\, [N/\mu m]$. + +*** Resonance Frequency +The resonance frequency is specified to be between 650Hz and 840Hz. +This is also the case for the FEM model (Figure ref:fig:apa300ml_resonance). + +#+begin_src matlab :exports none + freqs = logspace(2, 4, 5000); + + figure; + hold on; + plot(freqs, abs(squeeze(freqresp(G, freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + xlabel('Frequency [Hz]'); ylabel('Amplitude'); + hold off; +#+end_src + +#+begin_src matlab :tangle no :exports results :results file replace + exportFig('figs/apa300ml_resonance.pdf', 'width', 'wide', 'height', 'normal'); +#+end_src + +#+name: fig:apa300ml_resonance +#+caption: First resonance is around 800Hz +#+RESULTS: +[[file:figs/apa300ml_resonance.png]] + +*** Amplification factor +The amplification factor is the ratio of the vertical displacement to the stack displacement. + +#+begin_src matlab :exports none + %% Name of the Simulink File + mdl = 'APA300ML'; + + %% Input/Output definition + clear io; io_i = 1; + io(io_i) = linio([mdl, '/F'], 1, 'openinput'); io_i = io_i + 1; + io(io_i) = linio([mdl, '/z'], 1, 'openoutput'); io_i = io_i + 1; + io(io_i) = linio([mdl, '/d'], 1, 'openoutput'); io_i = io_i + 1; + + G = linearize(mdl, io); +#+end_src + +The ratio of the two displacement is computed from the FEM model. +#+begin_src matlab :results replace value + abs(dcgain(G(1,1))./dcgain(G(2,1))) +#+end_src + +#+RESULTS: +: 5.0749 + +This is actually correct and approximately corresponds to the ratio of the piezo height and length: +#+begin_src matlab :results replace value + 75/15 +#+end_src + +#+RESULTS: +: 5 + +*** Stroke + +Estimation of the actuator stroke: +\[ \Delta H = A n \Delta L \] +with: +- $\Delta H$ Axial Stroke of the APA +- $A$ Amplification factor (5 for the APA300ML) +- $n$ Number of stack used +- $\Delta L$ Stroke of the stack (0.1% of its length) + +#+begin_src matlab :results replace value + 1e6 * 5 * 3 * 20e-3 * 0.1e-2 +#+end_src + +#+RESULTS: +: 300 + +This is exactly the specified stroke in the data-sheet. + +*** TODO Stroke BIS +- [ ] Identified the stroke form the transfer function from V to z + +#+begin_src matlab :exports none + %% Name of the Simulink File + mdl = 'APA300ML'; + + %% Input/Output definition + clear io; io_i = 1; + io(io_i) = linio([mdl, '/V'], 1, 'openinput'); io_i = io_i + 1; + io(io_i) = linio([mdl, '/d'], 1, 'openoutput'); io_i = io_i + 1; + + G = linearize(mdl, io); + + 1e6*170*abs(dcgain(G)) +#+end_src + +** Identification of the Dynamics from actuator to replace displacement +We first set the mass to be approximately zero. +#+begin_src matlab :exports none + m = 0.01; +#+end_src + +The dynamics is identified from the applied force to the measured relative displacement. +#+begin_src matlab :exports none + %% Name of the Simulink File + mdl = 'APA300ML'; + + %% Input/Output definition + clear io; io_i = 1; + io(io_i) = linio([mdl, '/F'], 1, 'openinput'); io_i = io_i + 1; + io(io_i) = linio([mdl, '/z'], 1, 'openoutput'); io_i = io_i + 1; + + Gh = -linearize(mdl, io); +#+end_src + +The same dynamics is identified for a payload mass of 10Kg. +#+begin_src matlab + m = 10; +#+end_src + +#+begin_src matlab :exports none + %% Name of the Simulink File + mdl = 'APA300ML'; + + %% Input/Output definition + clear io; io_i = 1; + io(io_i) = linio([mdl, '/F'], 1, 'openinput'); io_i = io_i + 1; + io(io_i) = linio([mdl, '/z'], 1, 'openoutput'); io_i = io_i + 1; + + Ghm = -linearize(mdl, io); +#+end_src + +#+begin_src matlab :exports none + freqs = logspace(0, 4, 5000); + + figure; + tiledlayout(3, 1, 'TileSpacing', 'Compact', 'Padding', 'None'); + + ax1 = nexttile([2,1]); + hold on; + plot(freqs, abs(squeeze(freqresp(Gh, freqs, 'Hz'))), '-'); + plot(freqs, abs(squeeze(freqresp(Ghm, freqs, 'Hz'))), '-'); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + ylabel('Amplitude'); set(gca, 'XTickLabel',[]); + hold off; + + ax2 = nexttile; + hold on; + plot(freqs, 180/pi*unwrap(angle(squeeze(freqresp(Gh, freqs, 'Hz')))), '-', ... + 'DisplayName', '$m = 0kg$'); + plot(freqs, 180/pi*unwrap(angle(squeeze(freqresp(Ghm, freqs, 'Hz')))), '-', ... + 'DisplayName', '$m = 10kg$'); + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); + yticks(-360:90:360); + ylim([-360 0]); + xlabel('Frequency [Hz]'); ylabel('Phase [deg]'); + hold off; + linkaxes([ax1,ax2],'x'); + xlim([freqs(1), freqs(end)]); + legend('location', 'southwest'); +#+end_src + +#+begin_src matlab :tangle no :exports results :results file replace + exportFig('figs/apa300ml_plant_dynamics.pdf', 'width', 'wide', 'height', 'tall'); +#+end_src + +#+name: fig:apa300ml_plant_dynamics +#+caption: Transfer function from forces applied by the stack to the axial displacement of the APA +#+RESULTS: +[[file:figs/apa300ml_plant_dynamics.png]] + +The root locus corresponding to Direct Velocity Feedback with a mass of 10kg is shown in Figure ref:fig:apa300ml_dvf_root_locus. +#+begin_src matlab :exports none + figure; + + gains = logspace(0, 5, 500); + + hold on; + plot(real(pole(Ghm)), imag(pole(G)), 'kx'); + plot(real(tzero(Ghm)), imag(tzero(G)), 'ko'); + for k = 1:length(gains) + cl_poles = pole(feedback(Ghm, gains(k)*s)); + plot(real(cl_poles), imag(cl_poles), 'k.'); + end + hold off; + axis square; + xlim([-500, 10]); ylim([0, 510]); + + xlabel('Real Part'); ylabel('Imaginary Part'); +#+end_src + +#+begin_src matlab :tangle no :exports results :results file replace + exportFig('figs/apa300ml_dvf_root_locus.pdf', 'width', 'wide', 'height', 'tall'); +#+end_src + +#+name: fig:apa300ml_dvf_root_locus +#+caption: Root Locus for Direct Velocity Feedback +#+RESULTS: +[[file:figs/apa300ml_dvf_root_locus.png]] + +** Identification of the Dynamics from actuator to force sensor +Let's use 2 stacks as a force sensor and 1 stack as force actuator. + +The transfer function from actuator voltage to sensor voltage is identified and shown in Figure ref:fig:apa300ml_iff_plant. +#+begin_src matlab :exports none + m = 10; +#+end_src + +#+begin_src matlab :exports none + %% Name of the Simulink File + mdl = 'APA300ML'; + + %% Input/Output definition + clear io; io_i = 1; + io(io_i) = linio([mdl, '/Va'], 1, 'openinput'); io_i = io_i + 1; + io(io_i) = linio([mdl, '/Vs'], 1, 'openoutput'); io_i = io_i + 1; + + Giff = -linearize(mdl, io); +#+end_src + +#+begin_src matlab :exports none + freqs = logspace(0, 4, 5000); + + figure; + tiledlayout(3, 1, 'TileSpacing', 'Compact', 'Padding', 'None'); + + ax1 = nexttile([2,1]); + hold on; + plot(freqs, abs(squeeze(freqresp(Giff, freqs, 'Hz'))), '-'); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + ylabel('Amplitude'); set(gca, 'XTickLabel',[]); + hold off; + + ax2 = nexttile; + hold on; + plot(freqs, 180/pi*unwrap(angle(squeeze(freqresp(Giff, freqs, 'Hz')))), '-'); + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); + yticks(-360:90:360); + ylim([-180 180]); + xlabel('Frequency [Hz]'); ylabel('Phase [deg]'); + hold off; + linkaxes([ax1,ax2],'x'); + xlim([freqs(1), freqs(end)]); +#+end_src + +#+begin_src matlab :tangle no :exports results :results file replace + exportFig('figs/apa300ml_iff_plant.pdf', 'width', 'wide', 'height', 'tall'); +#+end_src + +#+name: fig:apa300ml_iff_plant +#+caption: Transfer function from actuator to force sensor +#+RESULTS: +[[file:figs/apa300ml_iff_plant.png]] + +For root locus corresponding to IFF is shown in Figure ref:fig:apa300ml_iff_root_locus. +#+begin_src matlab :exports none + figure; + + gains = logspace(0, 5, 500); + + hold on; + plot(real(pole(Giff)), imag(pole(Giff)), 'kx'); + plot(real(tzero(Giff)), imag(tzero(Giff)), 'ko'); + for k = 1:length(gains) + cl_poles = pole(feedback(Giff, gains(k)/s)); + plot(real(cl_poles), imag(cl_poles), 'k.'); + end + hold off; + axis square; + xlim([-500, 10]); ylim([0, 510]); + + xlabel('Real Part'); ylabel('Imaginary Part'); +#+end_src + +#+begin_src matlab :tangle no :exports results :results file replace + exportFig('figs/apa300ml_iff_root_locus.pdf', 'width', 'wide', 'height', 'tall'); +#+end_src + +#+name: fig:apa300ml_iff_root_locus +#+caption: Root Locus for IFF +#+RESULTS: +[[file:figs/apa300ml_iff_root_locus.png]] + +** Identification for a simpler model +The goal in this section is to identify the parameters of a simple APA model from the FEM. +This can be useful is a lower order model is to be used for simulations. + +The presented model is based on cite:souleille18_concep_activ_mount_space_applic. + +The model represents the Amplified Piezo Actuator (APA) from Cedrat-Technologies (Figure ref:fig:souleille18_model_piezo). +The parameters are shown in the table below. + +#+name: fig:souleille18_model_piezo +#+caption: Picture of an APA100M from Cedrat Technologies. Simplified model of a one DoF payload mounted on such isolator +[[file:./figs/souleille18_model_piezo.png]] + +#+caption:Parameters used for the model of the APA 100M +| | Meaning | +|-------+----------------------------------------------------------------| +| $k_e$ | Stiffness used to adjust the pole of the isolator | +| $k_1$ | Stiffness of the metallic suspension when the stack is removed | +| $k_a$ | Stiffness of the actuator | +| $c_1$ | Added viscous damping | + +The goal is to determine $k_e$, $k_a$ and $k_1$ so that the simplified model fits the FEM model. + +\[ \alpha = \frac{x_1}{f}(\omega=0) = \frac{\frac{k_e}{k_e + k_a}}{k_1 + \frac{k_e k_a}{k_e + k_a}} \] +\[ \beta = \frac{x_1}{F}(\omega=0) = \frac{1}{k_1 + \frac{k_e k_a}{k_e + k_a}} \] + +If we can fix $k_a$, we can determine $k_e$ and $k_1$ with: +\[ k_e = \frac{k_a}{\frac{\beta}{\alpha} - 1} \] +\[ k_1 = \frac{1}{\beta} - \frac{k_e k_a}{k_e + k_a} \] + +#+begin_src matlab :exports none + m = 10; +#+end_src + +#+begin_src matlab :exports none + %% Name of the Simulink File + mdl = 'APA300ML'; + + %% Input/Output definition + clear io; io_i = 1; + io(io_i) = linio([mdl, '/Fd'], 1, 'openinput'); io_i = io_i + 1; % External Vertical Force [N] + io(io_i) = linio([mdl, '/w'], 1, 'openinput'); io_i = io_i + 1; % Base Motion [m] + io(io_i) = linio([mdl, '/Fa'], 1, 'openinput'); io_i = io_i + 1; % Actuator Force [N] + io(io_i) = linio([mdl, '/z'], 1, 'openoutput'); io_i = io_i + 1; % Vertical Displacement [m] + io(io_i) = linio([mdl, '/Vs'], 1, 'openoutput'); io_i = io_i + 1; % Force Sensor [V] + io(io_i) = linio([mdl, '/d'], 1, 'openoutput'); io_i = io_i + 1; % Stack Displacement [m] + + G = linearize(mdl, io); + + G.InputName = {'Fd', 'w', 'Fa'}; + G.OutputName = {'y', 'Fs', 'd'}; +#+end_src + +From the identified dynamics, compute $\alpha$ and $\beta$ +#+begin_src matlab + alpha = abs(dcgain(G('y', 'Fa'))); + beta = abs(dcgain(G('y', 'Fd'))); +#+end_src + +$k_a$ is estimated using the following formula: +#+begin_src matlab + ka = 0.8/abs(dcgain(G('y', 'Fa'))); +#+end_src +The factor can be adjusted to better match the curves. + +Then $k_e$ and $k_1$ are computed. +#+begin_src matlab + ke = ka/(beta/alpha - 1); + k1 = 1/beta - ke*ka/(ke + ka); +#+end_src + +#+begin_src matlab :exports results :results value table replace :tangle no :post addhdr(*this*) + data2orgtable(1e-6*[ka; ke; k1], {'ka', 'ke', 'k1'}, {'Value [N/um]'}, ' %.1f '); +#+end_src + +#+RESULTS: +| | Value [N/um] | +|----+--------------| +| ka | 40.5 | +| ke | 1.5 | +| k1 | 0.4 | + +The damping in the system is adjusted to match the FEM model if necessary. +#+begin_src matlab + c1 = 1e2; +#+end_src + +The analytical model of the simpler system is defined below: +#+begin_src matlab + Ga = 1/(m*s^2 + k1 + c1*s + ke*ka/(ke + ka)) * ... + [ 1 , k1 + c1*s + ke*ka/(ke + ka) , ke/(ke + ka) ; + -ke*ka/(ke + ka), ke*ka/(ke + ka)*m*s^2 , -ke/(ke + ka)*(m*s^2 + c1*s + k1)]; + + Ga.InputName = {'Fd', 'w', 'Fa'}; + Ga.OutputName = {'y', 'Fs'}; +#+end_src + +And the DC gain is adjusted for the force sensor: +#+begin_src matlab + F_gain = dcgain(G('Fs', 'Fd'))/dcgain(Ga('Fs', 'Fd')); +#+end_src + +The dynamics of the FEM model and the simpler model are compared in Figure ref:fig:apa300ml_comp_simpler_model. + +#+begin_src matlab :exports none + freqs = logspace(0, 5, 1000); + + figure; + tiledlayout(2, 3, 'TileSpacing', 'Compact', 'Padding', 'None'); + + ax1 = nexttile; + hold on; + plot(freqs, abs(squeeze(freqresp(G( 'y', 'w'), freqs, 'Hz')))); + plot(freqs, abs(squeeze(freqresp(Ga('y', 'w'), freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + set(gca, 'XTickLabel',[]); + ylabel('$x_1/w$ [m/m]'); + ylim([1e-6, 1e2]); + + ax2 = nexttile; + hold on; + plot(freqs, abs(squeeze(freqresp(G( 'y', 'Fa'), freqs, 'Hz')))); + plot(freqs, abs(squeeze(freqresp(Ga('y', 'Fa'), freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + set(gca, 'XTickLabel',[]); + ylabel('$x_1/f$ [m/N]'); + ylim([1e-14, 1e-6]); + + ax3 = nexttile; + hold on; + plot(freqs, abs(squeeze(freqresp(G( 'y', 'Fd'), freqs, 'Hz')))); + plot(freqs, abs(squeeze(freqresp(Ga('y', 'Fd'), freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + set(gca, 'XTickLabel',[]); + ylabel('$x_1/F$ [m/N]'); + ylim([1e-14, 1e-4]); + + ax4 = nexttile; + hold on; + plot(freqs, abs(squeeze(freqresp(G( 'Fs', 'w'), freqs, 'Hz')))); + plot(freqs, abs(squeeze(freqresp(F_gain*Ga('Fs', 'w'), freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + xlabel('Frequency [Hz]'); + ylabel('$F_s/w$ [m/m]'); + ylim([1e2, 1e8]); + + ax5 = nexttile; + hold on; + plot(freqs, abs(squeeze(freqresp(G( 'Fs', 'Fa'), freqs, 'Hz')))); + plot(freqs, abs(squeeze(freqresp(F_gain*Ga('Fs', 'Fa'), freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + xlabel('Frequency [Hz]'); + ylabel('$F_s/f$ [m/N]'); + ylim([1e-4, 1e1]); + + ax6 = nexttile; + hold on; + plot(freqs, abs(squeeze(freqresp(G( 'Fs', 'Fd'), freqs, 'Hz')))); + plot(freqs, abs(squeeze(freqresp(F_gain*Ga('Fs', 'Fd'), freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + xlabel('Frequency [Hz]'); + ylabel('$F_s/F$ [m/N]'); + ylim([1e-7, 1e2]); + + linkaxes([ax1,ax2,ax3,ax4,ax5,ax6],'x'); +#+end_src + +#+begin_src matlab :tangle no :exports results :results file replace + exportFig('figs/apa300ml_comp_simpler_model.pdf', 'width', 'full', 'height', 'full'); +#+end_src + +#+name: fig:apa300ml_comp_simpler_model +#+caption: Comparison of the Dynamics between the FEM model and the simplified one +#+RESULTS: +[[file:figs/apa300ml_comp_simpler_model.png]] + +The simplified model has also been implemented in Simscape. + +The dynamics of the Simscape simplified model is identified and compared with the FEM one in Figure ref:fig:apa300ml_comp_simpler_simscape. +#+begin_src matlab :exports none + %% Name of the Simulink File + mdl = 'APA300ML_simplified'; + + %% Input/Output definition + clear io; io_i = 1; + io(io_i) = linio([mdl, '/Fd'], 1, 'openinput'); io_i = io_i + 1; % External Vertical Force [N] + io(io_i) = linio([mdl, '/w'], 1, 'openinput'); io_i = io_i + 1; % Base Motion [m] + io(io_i) = linio([mdl, '/Fa'], 1, 'openinput'); io_i = io_i + 1; % Actuator Force [N] + io(io_i) = linio([mdl, '/y'], 1, 'openoutput'); io_i = io_i + 1; % Vertical Displacement [m] + io(io_i) = linio([mdl, '/Fs'], 1, 'openoutput'); io_i = io_i + 1; % Force Sensor [V] + + Gs = linearize(mdl, io); + + Gs.InputName = {'Fd', 'w', 'Fa'}; + Gs.OutputName = {'y', 'Fs'}; +#+end_src + +#+begin_src matlab :exports none + freqs = logspace(0, 5, 1000); + + figure; + tiledlayout(2, 3, 'TileSpacing', 'Compact', 'Padding', 'None'); + + ax1 = nexttile; + hold on; + plot(freqs, abs(squeeze(freqresp(G( 'y', 'w'), freqs, 'Hz')))); + plot(freqs, abs(squeeze(freqresp(Gs('y', 'w'), freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + set(gca, 'XTickLabel',[]); + ylabel('$x_1/w$ [m/m]'); + ylim([1e-6, 1e2]); + + ax2 = nexttile; + hold on; + plot(freqs, abs(squeeze(freqresp(G( 'y', 'Fa'), freqs, 'Hz')))); + plot(freqs, abs(squeeze(freqresp(Gs('y', 'Fa'), freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + set(gca, 'XTickLabel',[]); + ylabel('$x_1/f$ [m/N]'); + ylim([1e-14, 1e-6]); + + ax3 = nexttile; + hold on; + plot(freqs, abs(squeeze(freqresp(G( 'y', 'Fd'), freqs, 'Hz')))); + plot(freqs, abs(squeeze(freqresp(Gs('y', 'Fd'), freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + set(gca, 'XTickLabel',[]); + ylabel('$x_1/F$ [m/N]'); + ylim([1e-14, 1e-4]); + + ax4 = nexttile; + hold on; + plot(freqs, abs(squeeze(freqresp(G( 'Fs', 'w'), freqs, 'Hz')))); + plot(freqs, abs(squeeze(freqresp(F_gain*Gs('Fs', 'w'), freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + xlabel('Frequency [Hz]'); + ylabel('$F_s/w$ [m/m]'); + ylim([1e2, 1e8]); + + ax5 = nexttile; + hold on; + plot(freqs, abs(squeeze(freqresp(G( 'Fs', 'Fa'), freqs, 'Hz')))); + plot(freqs, abs(squeeze(freqresp(F_gain*Gs('Fs', 'Fa'), freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + xlabel('Frequency [Hz]'); + ylabel('$F_s/f$ [m/N]'); + ylim([1e-4, 1e1]); + + ax6 = nexttile; + hold on; + plot(freqs, abs(squeeze(freqresp(G( 'Fs', 'Fd'), freqs, 'Hz')))); + plot(freqs, abs(squeeze(freqresp(F_gain*Gs('Fs', 'Fd'), freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + xlabel('Frequency [Hz]'); + ylabel('$F_s/F$ [m/N]'); + ylim([1e-7, 1e2]); + + linkaxes([ax1,ax2,ax3,ax4,ax5,ax6],'x'); +#+end_src + +#+begin_src matlab :tangle no :exports results :results file replace + exportFig('figs/apa300ml_comp_simpler_simscape.pdf', 'width', 'full', 'height', 'full'); +#+end_src + +#+name: fig:apa300ml_comp_simpler_simscape +#+caption: Comparison of the Dynamics between the FEM model and the simplified simscape model +#+RESULTS: +[[file:figs/apa300ml_comp_simpler_simscape.png]] + +** Integral Force Feedback +In this section, Integral Force Feedback control architecture is applied on the APA300ML. + +First, the plant (dynamics from voltage actuator to voltage sensor is identified). +#+begin_src matlab :exports none + Kiff = tf(0); +#+end_src + +The payload mass is set to 10kg. +#+begin_src matlab + m = 10; +#+end_src + +#+begin_src matlab :exports none + %% Name of the Simulink File + mdl = 'APA300ML_IFF'; + + %% Input/Output definition + clear io; io_i = 1; + io(io_i) = linio([mdl, '/w'], 1, 'openinput'); io_i = io_i + 1; + io(io_i) = linio([mdl, '/F'], 1, 'openinput'); io_i = io_i + 1; + io(io_i) = linio([mdl, '/Fd'], 1, 'openinput'); io_i = io_i + 1; + io(io_i) = linio([mdl, '/z'], 1, 'openoutput'); io_i = io_i + 1; + io(io_i) = linio([mdl, '/APA300ML'], 1, 'openoutput'); io_i = io_i + 1; + + G_ol = linearize(mdl, io); + G_ol.InputName = {'w', 'f', 'F'}; + G_ol.OutputName = {'x1', 'Fs'}; + + G = G_ol({'Fs'}, {'f'}); +#+end_src + +The obtained dynamics is shown in Figure ref:fig:piezo_amplified_iff_plant. + +#+begin_src matlab :exports none + freqs = logspace(1, 5, 1000); + + figure; + tiledlayout(3, 1, 'TileSpacing', 'Compact', 'Padding', 'None'); + + ax1 = nexttile([2,1]); + hold on; + plot(freqs, abs(squeeze(freqresp(G, freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + ylabel('Amplitude'); set(gca, 'XTickLabel',[]); + hold off; + + ax2 = nexttile; + hold on; + plot(freqs, 180/pi*unwrap(angle(squeeze(freqresp(G, freqs, 'Hz'))))); + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); + yticks(-360:90:360); + ylim([-390 30]); + xlabel('Frequency [Hz]'); ylabel('Phase [deg]'); + hold off; + linkaxes([ax1,ax2],'x'); + xlim([freqs(1), freqs(end)]); +#+end_src + +#+begin_src matlab :tangle no :exports results :results file replace + exportFig('figs/piezo_amplified_iff_plant.pdf', 'width', 'wide', 'height', 'tall'); +#+end_src + +#+name: fig:piezo_amplified_iff_plant +#+caption: IFF Plant +#+RESULTS: +[[file:figs/piezo_amplified_iff_plant.png]] + +The controller is defined below and the loop gain is shown in Figure ref:fig:piezo_amplified_iff_loop_gain. +#+begin_src matlab + Kiff = -1e3/s; +#+end_src + +#+begin_src matlab :exports none + freqs = logspace(1, 5, 1000); + + figure; + tiledlayout(3, 1, 'TileSpacing', 'Compact', 'Padding', 'None'); + + ax1 = nexttile([2,1]); + hold on; + plot(freqs, abs(squeeze(freqresp(G*Kiff, freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + ylabel('Amplitude'); set(gca, 'XTickLabel',[]); + hold off; + + ax2 = nexttile; + hold on; + plot(freqs, 180/pi*unwrap(angle(squeeze(freqresp(G*Kiff, freqs, 'Hz'))))); + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'lin'); + yticks(-360:90:360); + ylim([-180 180]); + xlabel('Frequency [Hz]'); ylabel('Phase [deg]'); + hold off; + linkaxes([ax1,ax2],'x'); + xlim([freqs(1), freqs(end)]); +#+end_src + +#+begin_src matlab :tangle no :exports results :results file replace + exportFig('figs/piezo_amplified_iff_loop_gain.pdf', 'width', 'wide', 'height', 'tall'); +#+end_src + +#+name: fig:piezo_amplified_iff_loop_gain +#+caption: IFF Loop Gain +#+RESULTS: +[[file:figs/piezo_amplified_iff_loop_gain.png]] + +Now the closed-loop system is identified again and compare with the open loop system in Figure ref:fig:piezo_amplified_iff_comp. + +It is the expected behavior as shown in the Figure ref:fig:souleille18_results (from cite:souleille18_concep_activ_mount_space_applic). + +#+begin_src matlab :exports none + clear io; io_i = 1; + io(io_i) = linio([mdl, '/w'], 1, 'openinput'); io_i = io_i + 1; + io(io_i) = linio([mdl, '/F'], 1, 'openinput'); io_i = io_i + 1; + io(io_i) = linio([mdl, '/Fd'], 1, 'openinput'); io_i = io_i + 1; + io(io_i) = linio([mdl, '/z'], 1, 'openoutput'); io_i = io_i + 1; + io(io_i) = linio([mdl, '/APA300ML'], 1, 'output'); io_i = io_i + 1; + + Giff = linearize(mdl, io); + Giff.InputName = {'w', 'f', 'F'}; + Giff.OutputName = {'x1', 'Fs'}; +#+end_src + +#+begin_src matlab :exports none + freqs = logspace(0, 3, 1000); + + figure; + tiledlayout(2, 3, 'TileSpacing', 'Compact', 'Padding', 'None'); + + ax1 = nexttile; + hold on; + plot(freqs, abs(squeeze(freqresp(G_ol('x1', 'w'), freqs, 'Hz')))); + plot(freqs, abs(squeeze(freqresp(Giff('x1', 'w'), freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + set(gca, 'XTickLabel',[]); ylabel('$x_1/w$ [m/m]') + + ax2 = nexttile; + hold on; + plot(freqs, abs(squeeze(freqresp(G_ol('x1', 'f'), freqs, 'Hz')))); + plot(freqs, abs(squeeze(freqresp(Giff('x1', 'f'), freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + set(gca, 'XTickLabel',[]); ylabel('$x_1/f$ [m/N]'); + + ax3 = nexttile; + hold on; + plot(freqs, abs(squeeze(freqresp(G_ol('x1', 'F'), freqs, 'Hz')))); + plot(freqs, abs(squeeze(freqresp(Giff('x1', 'F'), freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + set(gca, 'XTickLabel',[]); ylabel('$x_1/F$ [m/N]'); + + ax4 = nexttile; + hold on; + plot(freqs, abs(squeeze(freqresp(G_ol('Fs', 'w'), freqs, 'Hz')))); + plot(freqs, abs(squeeze(freqresp(Giff('Fs', 'w'), freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + xlabel('Frequency [Hz]'); ylabel('$F_s/w$ [N/m]'); + + ax5 = nexttile; + hold on; + plot(freqs, abs(squeeze(freqresp(G_ol('Fs', 'f'), freqs, 'Hz')))); + plot(freqs, abs(squeeze(freqresp(Giff('Fs', 'f'), freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + xlabel('Frequency [Hz]'); ylabel('$F_s/f$ [N/N]'); + + ax6 = nexttile; + hold on; + plot(freqs, abs(squeeze(freqresp(G_ol('Fs', 'F'), freqs, 'Hz')))); + plot(freqs, abs(squeeze(freqresp(Giff('Fs', 'F'), freqs, 'Hz')))); + hold off; + set(gca, 'XScale', 'log'); set(gca, 'YScale', 'log'); + xlabel('Frequency [Hz]'); ylabel('$F_s/F$ [N/N]'); + + linkaxes([ax1,ax2,ax3,ax4,ax5,ax6],'x'); +#+end_src + +#+begin_src matlab :tangle no :exports results :results file replace + exportFig('figs/piezo_amplified_iff_comp.pdf', 'width', 'full', 'height', 'full'); +#+end_src + +#+name: fig:piezo_amplified_iff_comp +#+caption: OL and CL transfer functions +#+RESULTS: +[[file:figs/piezo_amplified_iff_comp.png]] + +#+name: fig:souleille18_results +#+caption: Results obtained in cite:souleille18_concep_activ_mount_space_applic +[[file:figs/souleille18_results.png]] * Conclusion -<> +<> * Bibliography :ignore: #+latex: \printbibliography[heading=bibintoc,title={Bibliography}] @@ -3439,13 +3017,15 @@ exportFig('figs/philipp_tf_force_sensor_comp.pdf', 'width', 'half', 'height', 'n #+NAME: m-init-path #+BEGIN_SRC matlab %% Path for functions, data and scripts +addpath('./matlab/src/'); % Path for scripts addpath('./matlab/mat/'); % Path for data -addpath('./matlab/'); % Path for scripts +addpath('./matlab/'); #+END_SRC #+NAME: m-init-path-tangle #+BEGIN_SRC matlab %% Path for functions, data and scripts +addpath('./src/'); % Path for scripts addpath('./mat/'); % Path for data #+END_SRC @@ -3456,186 +3036,6 @@ addpath('./mat/'); % Path for data colors = colororder; #+END_SRC -** =initializeBotFlexibleJoint= - Initialize Flexible Joint -:PROPERTIES: -:header-args:matlab+: :tangle matlab/src/initializeBotFlexibleJoint.m -:header-args:matlab+: :comments none :mkdirp yes :eval no -:END: -<> - -*** Function description -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -function [flex_bot] = initializeBotFlexibleJoint(args) -% initializeBotFlexibleJoint - -% -% Syntax: [flex_bot] = initializeBotFlexibleJoint(args) -% -% Inputs: -% - args - -% -% Outputs: -% - flex_bot - -#+end_src - -*** Optional Parameters -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -arguments - args.type char {mustBeMember(args.type,{'2dof', '3dof', '4dof'})} = '2dof' - - args.kRx (6,1) double {mustBeNumeric, mustBePositive} = ones(6,1)*5 - args.kRy (6,1) double {mustBeNumeric, mustBePositive} = ones(6,1)*5 - args.kRz (6,1) double {mustBeNumeric, mustBePositive} = ones(6,1)*260 - args.kz (6,1) double {mustBeNumeric, mustBePositive} = ones(6,1)*7e7 - - args.cRx (6,1) double {mustBeNumeric, mustBePositive} = ones(6,1)*0.001 - args.cRy (6,1) double {mustBeNumeric, mustBePositive} = ones(6,1)*0.001 - args.cRz (6,1) double {mustBeNumeric, mustBePositive} = ones(6,1)*0.001 - args.cz (6,1) double {mustBeNumeric, mustBePositive} = ones(6,1)*0.001 -end -#+end_src - -*** Initialize the structure -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -flex_bot = struct(); -#+end_src - -*** Set the Joint's type -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -switch args.type - case '2dof' - flex_bot.type = 1; - case '3dof' - flex_bot.type = 2; - case '4dof' - flex_bot.type = 3; -end -#+end_src - -*** Set parameters -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -flex_bot.kRx = args.kRx; -flex_bot.kRy = args.kRy; -flex_bot.kRz = args.kRz; -flex_bot.kz = args.kz; -#+end_src - -#+begin_src matlab -flex_bot.cRx = args.cRx; -flex_bot.cRy = args.cRy; -flex_bot.cRz = args.cRz; -flex_bot.cz = args.cz; -#+end_src - -** =initializeTopFlexibleJoint= - Initialize Flexible Joint -:PROPERTIES: -:header-args:matlab+: :tangle matlab/src/initializeTopFlexibleJoint.m -:header-args:matlab+: :comments none :mkdirp yes :eval no -:END: -<> - -*** Function description -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -function [flex_top] = initializeTopFlexibleJoint(args) -% initializeTopFlexibleJoint - -% -% Syntax: [flex_top] = initializeTopFlexibleJoint(args) -% -% Inputs: -% - args - -% -% Outputs: -% - flex_top - -#+end_src - -*** Optional Parameters -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -arguments - args.type char {mustBeMember(args.type,{'2dof', '3dof', '4dof'})} = '2dof' - - args.kRx (6,1) double {mustBeNumeric, mustBePositive} = ones(6,1)*5 - args.kRy (6,1) double {mustBeNumeric, mustBePositive} = ones(6,1)*5 - args.kRz (6,1) double {mustBeNumeric, mustBePositive} = ones(6,1)*260 - args.kz (6,1) double {mustBeNumeric, mustBePositive} = ones(6,1)*7e7 - - args.cRx (6,1) double {mustBeNumeric, mustBePositive} = ones(6,1)*0.001 - args.cRy (6,1) double {mustBeNumeric, mustBePositive} = ones(6,1)*0.001 - args.cRz (6,1) double {mustBeNumeric, mustBePositive} = ones(6,1)*0.001 - args.cz (6,1) double {mustBeNumeric, mustBePositive} = ones(6,1)*0.001 -end -#+end_src - -*** Initialize the structure -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -flex_top = struct(); -#+end_src - -*** Set the Joint's type -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -switch args.type - case '2dof' - flex_top.type = 1; - case '3dof' - flex_top.type = 2; - case '4dof' - flex_top.type = 3; -end -#+end_src - -*** Set parameters -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -flex_top.kRx = args.kRx; -flex_top.kRy = args.kRy; -flex_top.kRz = args.kRz; -flex_top.kz = args.kz; -#+end_src - -#+begin_src matlab -flex_top.cRx = args.cRx; -flex_top.cRy = args.cRy; -flex_top.cRz = args.cRz; -flex_top.cz = args.cz; -#+end_src - ** =initializeAPA= - Initialize APA :PROPERTIES: :header-args:matlab+: :tangle matlab/src/initializeAPA.m @@ -3800,327 +3200,8 @@ actuator.ks = args.ks; % Stiffness of one stack [N/m] actuator.cs = args.cs; % Damping of one stack [N/m] #+end_src -** =generateSweepExc=: Generate sweep sinus excitation -:PROPERTIES: -:header-args:matlab+: :tangle ./matlab/src/generateSweepExc.m -:header-args:matlab+: :comments none :mkdirp yes :eval no -:END: -<> - -*** Function description -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -function [U_exc] = generateSweepExc(args) -% generateSweepExc - Generate a Sweep Sine excitation signal -% -% Syntax: [U_exc] = generateSweepExc(args) -% -% Inputs: -% - args - Optinal arguments: -% - Ts - Sampling Time - [s] -% - f_start - Start frequency of the sweep - [Hz] -% - f_end - End frequency of the sweep - [Hz] -% - V_mean - Mean value of the excitation voltage - [V] -% - V_exc - Excitation Amplitude for the Sweep, could be numeric or TF - [V] -% - t_start - Time at which the sweep begins - [s] -% - exc_duration - Duration of the sweep - [s] -% - sweep_type - 'logarithmic' or 'linear' - [-] -% - smooth_ends - 'true' or 'false': smooth transition between 0 and V_mean - [-] -#+end_src - -*** Optional Parameters -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -arguments - args.Ts (1,1) double {mustBeNumeric, mustBePositive} = 1e-4 - args.f_start (1,1) double {mustBeNumeric, mustBePositive} = 1 - args.f_end (1,1) double {mustBeNumeric, mustBePositive} = 1e3 - args.V_mean (1,1) double {mustBeNumeric} = 0 - args.V_exc = 1 - args.t_start (1,1) double {mustBeNumeric, mustBeNonnegative} = 5 - args.exc_duration (1,1) double {mustBeNumeric, mustBePositive} = 10 - args.sweep_type char {mustBeMember(args.sweep_type,{'log', 'lin'})} = 'lin' - args.smooth_ends logical {mustBeNumericOrLogical} = true -end -#+end_src - -*** Sweep Sine part -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -t_sweep = 0:args.Ts:args.exc_duration; - -if strcmp(args.sweep_type, 'log') - V_exc = sin(2*pi*args.f_start * args.exc_duration/log(args.f_end/args.f_start) * (exp(log(args.f_end/args.f_start)*t_sweep/args.exc_duration) - 1)); -elseif strcmp(args.sweep_type, 'lin') - V_exc = sin(2*pi*(args.f_start + (args.f_end - args.f_start)/2/args.exc_duration*t_sweep).*t_sweep); -else - error('sweep_type should either be equal to "log" or to "lin"'); -end -#+end_src - -#+begin_src matlab -if isnumeric(args.V_exc) - V_sweep = args.V_mean + args.V_exc*V_exc; -elseif isct(args.V_exc) - if strcmp(args.sweep_type, 'log') - V_sweep = args.V_mean + abs(squeeze(freqresp(args.V_exc, args.f_start*(args.f_end/args.f_start).^(t_sweep/args.exc_duration), 'Hz')))'.*V_exc; - elseif strcmp(args.sweep_type, 'lin') - V_sweep = args.V_mean + abs(squeeze(freqresp(args.V_exc, args.f_start+(args.f_end-args.f_start)/args.exc_duration*t_sweep, 'Hz')))'.*V_exc; - end -end -#+end_src - -*** Smooth Ends -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -if args.t_start > 0 - t_smooth_start = args.Ts:args.Ts:args.t_start; - - V_smooth_start = zeros(size(t_smooth_start)); - V_smooth_end = zeros(size(t_smooth_start)); - - if args.smooth_ends - Vd_max = args.V_mean/(0.7*args.t_start); - - V_d = zeros(size(t_smooth_start)); - V_d(t_smooth_start < 0.2*args.t_start) = t_smooth_start(t_smooth_start < 0.2*args.t_start)*Vd_max/(0.2*args.t_start); - V_d(t_smooth_start > 0.2*args.t_start & t_smooth_start < 0.7*args.t_start) = Vd_max; - V_d(t_smooth_start > 0.7*args.t_start & t_smooth_start < 0.9*args.t_start) = Vd_max - (t_smooth_start(t_smooth_start > 0.7*args.t_start & t_smooth_start < 0.9*args.t_start) - 0.7*args.t_start)*Vd_max/(0.2*args.t_start); - - V_smooth_start = cumtrapz(V_d)*args.Ts; - - V_smooth_end = args.V_mean - V_smooth_start; - end -else - V_smooth_start = []; - V_smooth_end = []; -end -#+end_src - -*** Combine Excitation signals -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -V_exc = [V_smooth_start, V_sweep, V_smooth_end]; -t_exc = args.Ts*[0:1:length(V_exc)-1]; -#+end_src - -#+begin_src matlab -U_exc = [t_exc; V_exc]; -#+end_src - -** =generateShapedNoise=: Generate Shaped Noise excitation -:PROPERTIES: -:header-args:matlab+: :tangle ./matlab/src/generateShapedNoise.m -:header-args:matlab+: :comments none :mkdirp yes :eval no -:END: -<> - -*** Function description -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -function [U_exc] = generateShapedNoise(args) -% generateShapedNoise - Generate a Shaped Noise excitation signal -% -% Syntax: [U_exc] = generateShapedNoise(args) -% -% Inputs: -% - args - Optinal arguments: -% - Ts - Sampling Time - [s] -% - V_mean - Mean value of the excitation voltage - [V] -% - V_exc - Excitation Amplitude, could be numeric or TF - [V rms] -% - t_start - Time at which the noise begins - [s] -% - exc_duration - Duration of the noise - [s] -% - smooth_ends - 'true' or 'false': smooth transition between 0 and V_mean - [-] -#+end_src - -*** Optional Parameters -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -arguments - args.Ts (1,1) double {mustBeNumeric, mustBePositive} = 1e-4 - args.V_mean (1,1) double {mustBeNumeric} = 0 - args.V_exc = 1 - args.t_start (1,1) double {mustBeNumeric, mustBePositive} = 5 - args.exc_duration (1,1) double {mustBeNumeric, mustBePositive} = 10 - args.smooth_ends logical {mustBeNumericOrLogical} = true -end -#+end_src - -*** Shaped Noise -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -t_noise = 0:args.Ts:args.exc_duration; - -#+end_src - -#+begin_src matlab -if isnumeric(args.V_exc) - V_noise = args.V_mean + args.V_exc*sqrt(1/args.Ts/2)*randn(length(t_noise), 1)'; -elseif isct(args.V_exc) - V_noise = args.V_mean + lsim(args.V_exc, sqrt(1/args.Ts/2)*randn(length(t_noise), 1), t_noise)'; -end -#+end_src - -*** Smooth Ends -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -t_smooth_start = args.Ts:args.Ts:args.t_start; - -V_smooth_start = zeros(size(t_smooth_start)); -V_smooth_end = zeros(size(t_smooth_start)); - -if args.smooth_ends - Vd_max = args.V_mean/(0.7*args.t_start); - - V_d = zeros(size(t_smooth_start)); - V_d(t_smooth_start < 0.2*args.t_start) = t_smooth_start(t_smooth_start < 0.2*args.t_start)*Vd_max/(0.2*args.t_start); - V_d(t_smooth_start > 0.2*args.t_start & t_smooth_start < 0.7*args.t_start) = Vd_max; - V_d(t_smooth_start > 0.7*args.t_start & t_smooth_start < 0.9*args.t_start) = Vd_max - (t_smooth_start(t_smooth_start > 0.7*args.t_start & t_smooth_start < 0.9*args.t_start) - 0.7*args.t_start)*Vd_max/(0.2*args.t_start); - - V_smooth_start = cumtrapz(V_d)*args.Ts; - - V_smooth_end = args.V_mean - V_smooth_start; -end -#+end_src - -*** Combine Excitation signals -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -V_exc = [V_smooth_start, V_noise, V_smooth_end]; -t_exc = args.Ts*[0:1:length(V_exc)-1]; -#+end_src - -#+begin_src matlab -U_exc = [t_exc; V_exc]; -#+end_src - -** =generateSinIncreasingAmpl=: Generate Sinus with increasing amplitude -:PROPERTIES: -:header-args:matlab+: :tangle ./matlab/src/generateSinIncreasingAmpl.m -:header-args:matlab+: :comments none :mkdirp yes :eval no -:END: -<> - -*** Function description -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -function [U_exc] = generateSinIncreasingAmpl(args) -% generateSinIncreasingAmpl - Generate Sinus with increasing amplitude -% -% Syntax: [U_exc] = generateSinIncreasingAmpl(args) -% -% Inputs: -% - args - Optinal arguments: -% - Ts - Sampling Time - [s] -% - V_mean - Mean value of the excitation voltage - [V] -% - sin_ampls - Excitation Amplitudes - [V] -% - sin_freq - Excitation Frequency - [Hz] -% - sin_num - Number of period for each amplitude - [-] -% - t_start - Time at which the excitation begins - [s] -% - smooth_ends - 'true' or 'false': smooth transition between 0 and V_mean - [-] -#+end_src - -*** Optional Parameters -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -arguments - args.Ts (1,1) double {mustBeNumeric, mustBePositive} = 1e-4 - args.V_mean (1,1) double {mustBeNumeric} = 0 - args.sin_ampls double {mustBeNumeric, mustBePositive} = [0.1, 0.2, 0.3] - args.sin_period (1,1) double {mustBeNumeric, mustBePositive} = 1 - args.sin_num (1,1) double {mustBeNumeric, mustBePositive, mustBeInteger} = 3 - args.t_start (1,1) double {mustBeNumeric, mustBePositive} = 5 - args.smooth_ends logical {mustBeNumericOrLogical} = true -end -#+end_src - -*** Sinus excitation -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -t_noise = 0:args.Ts:args.sin_period*args.sin_num; -sin_exc = []; -#+end_src - -#+begin_src matlab -for sin_ampl = args.sin_ampls - sin_exc = [sin_exc, args.V_mean + sin_ampl*sin(2*pi/args.sin_period*t_noise)]; -end -#+end_src - -*** Smooth Ends -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -t_smooth_start = args.Ts:args.Ts:args.t_start; - -V_smooth_start = zeros(size(t_smooth_start)); -V_smooth_end = zeros(size(t_smooth_start)); - -if args.smooth_ends - Vd_max = args.V_mean/(0.7*args.t_start); - - V_d = zeros(size(t_smooth_start)); - V_d(t_smooth_start < 0.2*args.t_start) = t_smooth_start(t_smooth_start < 0.2*args.t_start)*Vd_max/(0.2*args.t_start); - V_d(t_smooth_start > 0.2*args.t_start & t_smooth_start < 0.7*args.t_start) = Vd_max; - V_d(t_smooth_start > 0.7*args.t_start & t_smooth_start < 0.9*args.t_start) = Vd_max - (t_smooth_start(t_smooth_start > 0.7*args.t_start & t_smooth_start < 0.9*args.t_start) - 0.7*args.t_start)*Vd_max/(0.2*args.t_start); - - V_smooth_start = cumtrapz(V_d)*args.Ts; - - V_smooth_end = args.V_mean - V_smooth_start; -end -#+end_src - -*** Combine Excitation signals -:PROPERTIES: -:UNNUMBERED: t -:END: - -#+begin_src matlab -V_exc = [V_smooth_start, sin_exc, V_smooth_end]; -t_exc = args.Ts*[0:1:length(V_exc)-1]; -#+end_src - -#+begin_src matlab -U_exc = [t_exc; V_exc]; -#+end_src +* Footnotes +[fn:4]The Matlab =fminsearch= command is used to fit the plane +[fn:3]Heidenhain MT25, specified accuracy of $0.5\,\mu m$ +[fn:2]Millimar 1318 probe, specified linearity better than $1\,\mu m$ +[fn:1]LCR-819 from Gwinstek, specified accuracy of $0.05\%$, measured frequency is set at $1\,\text{kHz}$ diff --git a/test-bench-apa.pdf b/test-bench-apa.pdf index 359089a..ac9d86e 100644 Binary files a/test-bench-apa.pdf and b/test-bench-apa.pdf differ diff --git a/test-bench-apa.tex b/test-bench-apa.tex index 7b345c8..c8e36d5 100644 --- a/test-bench-apa.tex +++ b/test-bench-apa.tex @@ -1,4 +1,4 @@ -% Created 2024-03-19 Tue 17:22 +% Created 2024-03-21 Thu 18:12 % Intended LaTeX compiler: pdflatex \documentclass[a4paper, 10pt, DIV=12, parskip=full, bibliography=totoc]{scrreprt} @@ -22,181 +22,66 @@ \tableofcontents \clearpage +\begin{figure}[htbp] +\centering +\includegraphics[scale=1,width=0.7\linewidth]{figs/test_apa_received.jpg} +\caption{\label{fig:test_apa_received}Picture of 5 out of the 7 received APA300ML} +\end{figure} + The first goal is to characterize the APA300ML in terms of: \begin{itemize} \item The, geometric features, electrical capacitance, stroke, hysteresis, spurious resonances. -This is performed in Section \ref{sec:first_measurements}. +This is performed in Section \ref{sec:test_apa_basic_meas}. \item The dynamics from the generated DAC voltage (going to the voltage amplifiers and then applied on the actuator stacks) to the induced displacement, and to the measured voltage by the force sensor stack. Also the ``actuator constant'' and ``sensor constant'' are identified. -This is done in Section \ref{sec:dynamical_meas_apa}. +This is done in Section \ref{sec:test_apa_dynamics}. \item Compare the measurements with the Simscape models (2DoF, Super-Element) in order to tuned/validate the models. -This is explained in Section \ref{sec:simscape_bench_apa}. +This is explained in Section \ref{sec:test_apa_simscape}. \end{itemize} \begin{table}[htbp] -\caption{\label{tab:test_bench_apa_section_matlab_code}Report sections and corresponding Matlab files} +\caption{\label{tab:test_apa_section_matlab_code}Report sections and corresponding Matlab files} \centering \begin{tabularx}{0.6\linewidth}{lX} \toprule \textbf{Sections} & \textbf{Matlab File}\\ \midrule -Section \ref{sec:test_bench_apa}\_ & \texttt{test\_bench\_apa\_1\_.m}\\ +Section \ref{sec:test_apa_basic_meas} & \texttt{test\_apa\_1\_basic\_meas.m}\\ +Section \ref{sec:test_apa_dynamics} & \texttt{test\_apa\_2\_.m}\\ +Section \ref{sec:test_apa_simscape} & \texttt{test\_apa\_3\_.m}\\ \bottomrule \end{tabularx} \end{table} -\chapter{Model of the Amplified Piezoelectric Actuator} -\label{sec:model_apa} -The Amplified Piezoelectric Actuator (APA) used is the APA300ML from Cedrat technologies (Figure \ref{fig:apa300ML}). - -\begin{figure}[htbp] -\centering -\includegraphics[scale=1,width=0.8\linewidth]{figs/apa300ML.png} -\caption{\label{fig:apa300ML}Picture of the APA300ML} -\end{figure} - -Two simscape models of the APA300ML are developed: -\begin{itemize} -\item Section \ref{sec:apa_2dof_model}: a simple 2 degrees of freedom (DoF) model -\item Section \ref{sec:apa_flexible_model}: a ``flexible'' model using a ``super-element'' extracted from a Finite Element Model of the APA -\end{itemize} - -For both models, an ``actuator constant'' and a ``sensor constant'' are used. -These constants are used to link the electrical domain and the mechanical domain. -They are described in Section \ref{sec:apa_constants}. -\section{Two Degrees of Freedom Model} -\label{sec:apa_2dof_model} - -The presented model is based on \cite{souleille18_concep_activ_mount_space_applic} and represented in Figure \ref{fig:souleille18_model_piezo}. - -\begin{figure}[htbp] -\centering -\includegraphics[scale=1,width=0.6\linewidth]{./figs/souleille18_model_piezo.png} -\caption{\label{fig:souleille18_model_piezo}Picture of an APA100M from Cedrat Technologies. Simplified model of a one DoF payload mounted on such isolator} -\end{figure} - -The parameters are described in Table \ref{tab:souleille18_model_params}. - -\begin{table}[htbp] -\caption{\label{tab:souleille18_model_params}Parameters used for the model of the APA 100M} -\centering -\begin{tabularx}{0.6\linewidth}{lX} -\toprule - & \textbf{Meaning}\\ -\midrule -\(k_e\) & Stiffness used to adjust the pole of the isolator\\ -\(k_1\) & Stiffness of the metallic suspension when the stack is removed\\ -\(k_a\) & Stiffness of the actuator\\ -\(c_1\) & Added viscous damping\\ -\bottomrule -\end{tabularx} -\end{table} - -The model is shown again in Figure \ref{fig:2dof_apa_model}. -As will be shown in the next section, such model can be quite accurate in modelling the axial behavior of the APA. -However, it does not model the flexibility of the APA in the other directions. - -Therefore this model can be useful for quick simulations as it contains a very limited number of states, but when more complex dynamics of the APA is to be modelled, a flexible model will be used. - -\begin{figure}[htbp] -\centering -\includegraphics[scale=1,width=0.2\linewidth]{figs/2dof_apa_model.png} -\caption{\label{fig:2dof_apa_model}Schematic of the 2DoF model for the Amplified Piezoelectric Actuator} -\end{figure} -\section{Flexible Model} -\label{sec:apa_flexible_model} - -In order to model with high accuracy the behavior of the APA, a flexible model can be used. - -The idea is to do a Finite element model of the structure, and to defined ``remote points'' as shown in Figure \ref{fig:apa300ml_ansys}. -Then, on the finite element software, a ``super-element'' can be extracted which consists of a mass matrix, a stiffness matrix, and the coordinates of the remote points. - -\begin{figure}[htbp] -\centering -\includegraphics[scale=1,width=0.3\linewidth]{figs/mesh_APA.png} -\caption{\label{fig:apa300ml_ansys}Remote points for the APA300ML (Ansys)} -\end{figure} - -This ``super-element'' can then be included in the Simscape model as shown in Figure \ref{fig:figure_name}. -The remotes points are defined as ``frames'' in Simscape, and the ``super-element'' can be connected with other Simscape elements (mechanical joints, masses, force actuators, etc..). - -\begin{figure}[htbp] -\centering -\includegraphics[scale=1,width=\linewidth]{figs/super_element_simscape.png} -\caption{\label{fig:figure_name}From a finite Element Model (Ansys, bottom left) is extract the mass and stiffness matrices that are then used on Simscape (right)} -\end{figure} -\section{Actuator and Sensor constants} -\label{sec:apa_constants} - -On Simscape, we want to model both the actuator stacks and the sensors stack. -We therefore need to link the electrical domain (voltages, charges) with the mechanical domain (forces, strain). -To do so, we use the ``actuator constant'' and the ``sensor constant''. - -Consider a schematic of the Amplified Piezoelectric Actuator in Figure \ref{fig:apa_model_schematic}. - -\begin{figure}[htbp] -\centering -\includegraphics[scale=1,width=0.5\linewidth]{figs/apa_model_schematic.png} -\caption{\label{fig:apa_model_schematic}Amplified Piezoelectric Actuator Schematic} -\end{figure} - -A voltage \(V_a\) applied to the actuator stacks will induce an actuator force \(F_a\): -\begin{equation} - \boxed{F_a = g_a \cdot V_a} -\end{equation} - -A change of length \(dl\) of the sensor stack will induce a voltage \(V_s\): -\begin{equation} - \boxed{V_s = g_s \cdot dl} -\end{equation} - -The block-diagram model of the piezoelectric actuator is then as shown in Figure \ref{fig:apa-model-simscape-schematic}. - -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/apa-model-simscape-schematic.png} -\caption{\label{fig:apa-model-simscape-schematic}Model of the APA with Simscape/Simulink} -\end{figure} - -The constants \(g_a\) and \(g_s\) will be experimentally estimated. \chapter{First Basic Measurements} -\label{sec:first_measurements} +\label{sec:test_apa_basic_meas} Before using the measurement bench to characterize the APA300ML, first simple measurements are performed: \begin{itemize} -\item Section \ref{sec:geometrical_measurements}: the geometric tolerances of the interface planes are checked -\item Section \ref{sec:electrical_measurements}: the capacitance of the stacks are measured -\item Section \ref{sec:stroke_measurements}: the stroke of the APA are measured -\item Section \ref{sec:spurious_resonances}: the ``spurious'' resonances of the APA are investigated -\item Section \ref{sec:spurious_resonances_struts}: the ``spurious'' resonances of the struts are measured and compared with the FEM +\item Section \ref{sec:test_apa_geometrical_measurements}: the geometric tolerances of the interface planes are checked +\item Section \ref{sec:test_apa_electrical_measurements}: the capacitance of the piezoelectric stacks is measured +\item Section \ref{sec:test_apa_stroke_measurements}: the stroke of each APA is measured +\item Section \ref{sec:test_apa_spurious_resonances}: the ``spurious'' resonances of the APA are investigated \end{itemize} \section{Geometrical Measurements} -\label{sec:geometrical_measurements} -The received APA are shown in Figure \ref{fig:received_apa}. +\label{sec:test_apa_geometrical_measurements} + +To measure the flatness of the two mechanical interfaces of the APA300ML, a small measurement bench is installed on top of a metrology granite with very good flatness. + +As shown in Figure \ref{fig:test_apa_flatness_setup}, the APA is fixed to a clamp while a measuring probe\footnote{Heidenhain MT25, specified accuracy of \(0.5\,\mu m\)} is used to measure the height of 4 points on each of the APA300ML interfaces. + +From the X-Y-Z coordinates of the measured 8 points, the flatness is estimated by best fitting\footnote{The Matlab \texttt{fminsearch} command is used to fit the plane} a plane through all the points. \begin{figure}[htbp] \centering -\includegraphics[scale=1,width=0.9\linewidth]{figs/received_apa.jpg} -\caption{\label{fig:received_apa}Received APA} +\includegraphics[scale=1,width=0.4\linewidth]{figs/test_apa_flatness_setup.png} +\caption{\label{fig:test_apa_flatness_setup}Measurement setup for flatness estimation of the two mechanical interfaces} \end{figure} -\subsection{Measurement Setup} -The flatness corresponding to the two interface planes are measured as shown in Figure \ref{fig:flatness_meas_setup}. - -\begin{figure}[htbp] -\centering -\includegraphics[scale=1,width=0.8\linewidth]{figs/flatness_meas_setup.jpg} -\caption{\label{fig:flatness_meas_setup}Measurement Setup} -\end{figure} -\subsection{Measurement Results} - -The height (Z) measurements at the 8 locations (4 points by plane) are defined below. -The X/Y Positions of the 8 measurement points are defined below. -Finally, the flatness is estimated by fitting a plane through the 8 points using the \texttt{fminsearch} command. -The obtained flatness are shown in Table \ref{tab:flatness_meas}. +The measured flatness, summarized in Table \ref{tab:test_apa_flatness_meas}, are within the specifications. \begin{table}[htbp] -\caption{\label{tab:flatness_meas}Estimated flatness} +\caption{\label{tab:test_apa_flatness_meas}Estimated flatness of the APA300ML interfaces} \centering -\begin{tabularx}{0.25\linewidth}{lc} +\begin{tabularx}{0.3\linewidth}{Xc} \toprule & \textbf{Flatness} \([\mu m]\)\\ \midrule @@ -210,36 +95,29 @@ APA 7 & 18.7\\ \bottomrule \end{tabularx} \end{table} - -\begin{important} -The measured flatness of the APA300ML interface planes are within the specifications. -\end{important} \section{Electrical Measurements} -\label{sec:electrical_measurements} -\subsection{Measurement Setup} -\begin{note} -The capacitance of the stacks is measure with the \href{https://www.gwinstek.com/en-global/products/detail/LCR-800}{LCR-800 Meter} (\href{doc/DS\_LCR-800\_Series\_V2\_E.pdf}{doc}) shown in Figure \ref{fig:LCR_meter}. -The excitation frequency is set to be 1kHz. -\end{note} +\label{sec:test_apa_electrical_measurements} + +From the documentation of the APA300ML, the total capacitance of the three stacks should be between \(18\,\mu F\) and \(26\,\mu F\) with a nominal capacitance of \(20\,\mu F\). + +The capacitance of the piezoelectric stacks found in the APA300ML have been measured with the LCR meter\footnote{LCR-819 from Gwinstek, specified accuracy of \(0.05\%\), measured frequency is set at \(1\,\text{kHz}\)} shown in Figure \ref{fig:test_apa_lcr_meter}. +The two stacks used as an actuator and the stack used as a force sensor are measured separately. \begin{figure}[htbp] \centering -\includegraphics[scale=1,width=0.9\linewidth]{figs/LCR_meter.jpg} -\caption{\label{fig:LCR_meter}LCR Meter used for the measurements} +\includegraphics[scale=1,width=0.6\linewidth]{figs/test_apa_lcr_meter.jpg} +\caption{\label{fig:test_apa_lcr_meter}LCR Meter used for the measurements} \end{figure} -\subsection{Measured Capacitance} -From the documentation of the APA300ML, the total capacitance of the three stacks should be between \(18\mu F\) and \(26\mu F\) with a nominal capacitance of \(20\mu F\). -However, from the documentation of the stack themselves, it can be seen that the capacitance of a single stack should be \(4.4\mu F\). -Clearly, the total capacitance of the APA300ML if more than just three times the capacitance of one stack. -\begin{question} -Could it be possible that the capacitance of the stacks increase that much when they are pre-stressed? -\end{question} +The measured capacitance are summarized in Table \ref{tab:test_apa_capacitance} and the average capacitance of one stack is \(\approx 5 \mu F\). +However, the measured capacitance of the stacks of ``APA 3'' is only half of the expected capacitance. +This may indicate a manufacturing defect. -The measured capacitance of the stacks are summarized in Table \ref{tab:apa300ml_capacitance}. +The measured capacitance is found to be lower than the specified one. +This may be due to the fact that the manufacturer measures the capacitance with large signals (\(-20\,V\) to \(150\,V\)) while it was here measured with small signals. \begin{table}[htbp] -\caption{\label{tab:apa300ml_capacitance}Capacitance measured with the LCR meter. The excitation signal is a sinus at 1kHz} +\caption{\label{tab:test_apa_capacitance}Capacitance measured with the LCR meter. The excitation signal is a sinus at 1kHz} \centering \begin{tabularx}{0.5\linewidth}{lcc} \toprule @@ -255,128 +133,39 @@ APA 7 & 4.85 & 9.85\\ \bottomrule \end{tabularx} \end{table} +\section{Stroke Measurement} +\label{sec:test_apa_stroke_measurements} -\begin{important} -From the measurements (Table \ref{tab:apa300ml_capacitance}), the capacitance of one stack is found to be \(\approx 5 \mu F\). -\end{important} +The goal is here to verify that the stroke of the APA300ML is as specified in the datasheet. +To do so, one side of the APA is fixed to the granite, and a displacement probe\footnote{Millimar 1318 probe, specified linearity better than \(1\,\mu m\)} is located on the other side as shown in Figure \ref{fig:test_apa_stroke_bench}. -\begin{warning} -There is clearly a problem with APA300ML number 3 -The APA number 3 has ben sent back to Cedrat, and a new APA300ML has been shipped back. -\end{warning} -\section{Stroke measurement} -\label{sec:stroke_measurements} -We here wish to estimate the stroke of the APA. - -To do so, one side of the APA is fixed, and a displacement probe is located on the other side as shown in Figure \ref{fig:stroke_test_bench}. - -Then, a voltage is applied on either one or two stacks using a DAC and a voltage amplifier. - -\begin{note} -Here are the documentation of the equipment used for this test bench: -\begin{itemize} -\item \textbf{Voltage Amplifier}: \href{doc/PD200-V7-R1.pdf}{PD200} with a gain of 20 -\item \textbf{16bits DAC}: \href{doc/IO131-OEM-Datasheet.pdf}{IO313 Speedgoat card} -\item \textbf{Displacement Probe}: \href{doc/Millimar--3723046--BA--C1208-C1216-C1240--FR--2016-11-08.pdf}{Millimar C1216 electronics} and \href{doc/tmp3m0cvmue\_7888038c-cdc8-48d8-a837-35de02760685.pdf}{Millimar 1318 probe} -\end{itemize} -\end{note} +Then, the voltage across the two actuator stacks is varied from \(-20\,V\) to \(150\,V\) using a DAC and a voltage amplifier. +Note that the voltage is here slowly varied as the displacement probe has a very low measurement bandwidth (see Figure \ref{fig:test_apa_stroke_bench}, left). \begin{figure}[htbp] \centering -\includegraphics[scale=1,width=0.9\linewidth]{figs/stroke_test_bench.jpg} -\caption{\label{fig:stroke_test_bench}Bench to measured the APA stroke} +\includegraphics[scale=1,width=0.9\linewidth]{figs/test_apa_stroke_bench.jpg} +\caption{\label{fig:test_apa_stroke_bench}Bench to measured the APA stroke} \end{figure} -From the documentation, the nominal stroke of the APA300ML is \(304\,\mu m\). -\subsection{Voltage applied on one stack} +The measured APA displacement is shown as a function of the applied voltage in Figure \ref{fig:test_apa_stroke_result}, right. -Let's first look at the relation between the voltage applied to \textbf{one} stack to the displacement of the APA as measured by the displacement probe. +Typical hysteresis curves for piezoelectric stack actuators can be observed. +The measured stroke is approximately \(250\,\mu m\) when using only two of the three stacks, which is enough for the current application. +This is even above what is specified as the nominal stroke in the data-sheet (\(304\,\mu m\), therefore \(\approx 200\,\mu m\) if only two stacks are used). -The applied voltage is shown in Figure \ref{fig:apa_stroke_voltage_time}. +It is clear from Figure \ref{fig:test_apa_stroke_result} that ``APA 3'' has an issue compared to the other units. +This confirms the abnormal electrical measurements made in Section \ref{sec:test_apa_electrical_measurements}. +This unit was send sent back to Cedrat and a new one was shipped back. +From now on, only the six APA that behave as expected will be used. \begin{figure}[htbp] \centering -\includegraphics[scale=1]{figs/apa_stroke_voltage_time.png} -\caption{\label{fig:apa_stroke_voltage_time}Applied voltage as a function of time} +\includegraphics[scale=1]{figs/test_apa_stroke_result.png} +\caption{\label{fig:test_apa_stroke_result}Generated voltage across the two piezoelectric stack actuators to estimate the stroke of the APA300ML (left). Measured displacement as a function of the applied voltage (right)} \end{figure} - -The obtained displacements for all the APA are shown in Figure \ref{fig:apa_stroke_time_1s}. -The displacement is set to zero at initial time when the voltage applied is -20V. - -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/apa_stroke_time_1s.png} -\caption{\label{fig:apa_stroke_time_1s}Displacement as a function of time for all the APA300ML (only one stack is used as an actuator)} -\end{figure} - -Finally, the displacement is shown as a function of the applied voltage in Figure \ref{fig:apa_d_vs_V_1s}. -We can clearly see that there is a problem with the APA 3. -Also, there is a large hysteresis. - -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/apa_d_vs_V_1s.png} -\caption{\label{fig:apa_d_vs_V_1s}Displacement as a function of the applied voltage (on only one stack)} -\end{figure} - -\begin{important} -We can clearly confirm from Figure \ref{fig:apa_d_vs_V_1s} that there is a problem with the APA number 3. -\end{important} -\subsection{Voltage applied on two stacks} - -Now look at the relation between the voltage applied to the \textbf{two} other stacks to the displacement of the APA as measured by the displacement probe. - -The obtained displacement is shown in Figure \ref{fig:apa_stroke_time_2s}. -The displacement is set to zero at initial time when the voltage applied is -20V. -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/apa_stroke_time_2s.png} -\caption{\label{fig:apa_stroke_time_2s}Displacement as a function of time for all the APA300ML (two stacks are used as actuators)} -\end{figure} - -Finally, the displacement is shown as a function of the applied voltage in Figure \ref{fig:apa_d_vs_V_2s}. -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/apa_d_vs_V_2s.png} -\caption{\label{fig:apa_d_vs_V_2s}Displacement as a function of the applied voltage on two stacks} -\end{figure} -\subsection{Voltage applied on all three stacks} - -Finally, we can combine the two measurements to estimate the relation between the displacement and the voltage applied to the \textbf{three} stacks (Figure \ref{fig:apa_d_vs_V_3s}). - -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/apa_d_vs_V_3s.png} -\caption{\label{fig:apa_d_vs_V_3s}Displacement as a function of the applied voltage on all three stacks} -\end{figure} - -The obtained maximum stroke for all the APA are summarized in Table \ref{tab:apa_measured_stroke}. - -\begin{table}[htbp] -\caption{\label{tab:apa_measured_stroke}Measured maximum stroke} -\centering -\begin{tabularx}{0.25\linewidth}{lc} -\toprule - & \textbf{Stroke} \([\mu m]\)\\ -\midrule -APA 1 & 373.2\\ -APA 2 & 365.5\\ -APA 3 & 181.7\\ -APA 4 & 359.7\\ -APA 5 & 361.5\\ -APA 6 & 363.9\\ -APA 7 & 358.4\\ -\bottomrule -\end{tabularx} -\end{table} -\subsection{Conclusion} -\begin{important} -The except from APA 3 that has a problem, all the APA are similar when it comes to stroke and hysteresis. -Also, the obtained stroke is more than specified in the documentation. -Therefore, only two stacks can be used as an actuator. -\end{important} -\section{Spurious resonances - APA} -\label{sec:spurious_resonances} +\section{Spurious resonances - APA\hfill{}\textsc{@philipp}} +\label{sec:test_apa_spurious_resonances} \subsection{Introduction} From a Finite Element Model of the struts, it have been found that three main resonances are foreseen to be problematic for the control of the APA300ML (Figure \ref{fig:apa_mode_shapes_ter}): @@ -519,7 +308,7 @@ It is however quite interesting that there is a factor \(\approx \sqrt{2}\) betw \begin{table}[htbp] \caption{\label{tab:apa300ml_measured_modes_freq}Measured frequency of the modes} \centering -\begin{tabularx}{0.6\linewidth}{Xcc} +\begin{tabularx}{0.7\linewidth}{Xcc} \toprule \textbf{Mode} & \textbf{FEM - Strut mode} & \textbf{Measured Frequency}\\ \midrule @@ -530,456 +319,268 @@ Z-Torsion & 400Hz & 800Hz?\\ \end{tabularx} \end{table} \chapter{Dynamical measurements - APA} -\label{sec:dynamical_meas_apa} -In this section, a measurement test bench is used to extract all the important parameters of the Amplified Piezoelectric Actuator APA300ML. +\label{sec:test_apa_dynamics} -This include: -\begin{itemize} -\item Stroke -\item Stiffness -\item Hysteresis -\item ``Actuator constant'': Gain from the applied voltage \(V_a\) to the generated Force \(F_a\) -\item ``Sensor constant'': Gain from the sensor stack strain \(\delta L\) to the generated voltage \(V_s\) -\item Dynamical behavior from the actuator to the force sensor and to the motion of the APA -\end{itemize} +After the basic measurements on the APA were performed in Section \ref{sec:test_apa_basic_meas}, a new test bench is used to better characterize the APA. -The bench is shown in Figure \ref{fig:picture_apa_bench}, and a zoom picture on the APA and encoder is shown in Figure \ref{fig:picture_apa_bench_encoder}. +This test bench is shown in Figure \ref{fig:test_bench_apa} and consists of the APA300ML fixed on one end to the fixed granite, and on the other end to the 5kg granite vertically guided with an air bearing. +An encoder is used to measure the relative motion between the two granites (i.e. the displacement of the APA). -\begin{figure}[htbp] -\centering -\includegraphics[scale=1,width=0.5\linewidth]{figs/picture_apa_bench.jpg} -\caption{\label{fig:picture_apa_bench}Picture of the test bench} +\begin{figure} +\begin{subfigure}{0.3\textwidth} +\begin{center} +\includegraphics[scale=1,height=8cm]{figs/test_apa_bench_picture.jpg} +\end{center} +\subcaption{\label{fig:test_apa_bench_picture}Picture of the test bench} +\end{subfigure} +\begin{subfigure}{0.69\textwidth} +\begin{center} +\includegraphics[scale=1,height=8cm]{figs/test_apa_bench_picture_encoder.jpg} +\end{center} +\subcaption{\label{fig:test_apa_bench_picture_encoder}Zoom on the APA with the encoder} +\end{subfigure} +\caption{\label{fig:test_bench_apa}Test bench used to characterize the APA300ML} \end{figure} -\begin{figure}[htbp] -\centering -\includegraphics[scale=1,width=0.5\linewidth]{figs/picture_apa_bench_encoder.jpg} -\caption{\label{fig:picture_apa_bench_encoder}Zoom on the APA with the encoder} -\end{figure} - -The bench is schematically shown in Figure \ref{fig:test_bench_apa_alone} and the signal used are summarized in Table \ref{tab:test_bench_apa_variables}. +The bench is schematically shown in Figure \ref{fig:test_apa_schematic} and the signal used are summarized in Table \ref{tab:test_apa_variables}. \begin{figure}[htbp] \centering -\includegraphics[scale=1,width=0.8\linewidth]{figs/test_bench_apa_alone.png} -\caption{\label{fig:test_bench_apa_alone}Schematic of the Test Bench} +\includegraphics[scale=1,scale=1]{figs/test_apa_schematic.png} +\caption{\label{fig:test_apa_schematic}Schematic of the Test Bench} \end{figure} \begin{table}[htbp] -\caption{\label{tab:test_bench_apa_variables}Variables used during the measurements} +\caption{\label{tab:test_apa_variables}Variables used during the measurements} \centering -\begin{tabularx}{0.9\linewidth}{lllX} +\begin{tabularx}{0.6\linewidth}{cXc} \toprule -\textbf{Variable} & \textbf{Description} & \textbf{Unit} & \textbf{Hardware}\\ +\textbf{Variable} & \textbf{Description} & \textbf{Unit}\\ \midrule -\texttt{Va} & Output DAC voltage & {[}V] & DAC - Ch. 1 - PD200 - APA\\ -\texttt{Vs} & Measured stack voltage (ADC) & {[}V] & APA - ADC - Ch. 1\\ -\texttt{de} & Encoder Measurement & {[}m] & PEPU Ch. 1 - IO318(1) Ch. 1\\ -\texttt{da} & Attocube Measurement & {[}m] & PEPU Ch. 2 - IO318(1) Ch. 2\\ -\texttt{t} & Time & {[}s] & \\ +\(u\) & Output DAC Voltage & \(V\)\\ +\(V_a\) & Output Amplifier Voltage & \(V\)\\ +\(V_s\) & Measured Stack Voltage (ADC) & \(V\)\\ +\(d_e\) & Encoder Measurement & \(m\)\\ \bottomrule \end{tabularx} \end{table} -This section is structured as follows: +This bench will be used to: \begin{itemize} -\item Section \ref{sec:meas_one_apa}: the measurements are first performed on one APA. -\item Section \ref{sec:meas_all_apa}: the same measurements are performed on all the APA and are compared. -\end{itemize} -\section{Measurements on APA 1} -\label{sec:meas_one_apa} -Measurements are first performed on only \textbf{one} APA. -Once the measurement procedure is validated, it is performed on all the other APA. -\subsection{Excitation Signals} -Different excitation signals are used to perform FRF estimations. - -Typically, this is done in three steps: -\begin{enumerate} -\item A low pass filtered white noise is used with rather small amplitudes (Figure \ref{fig:exc_signal_1_noise}). -This first excitation is used to estimate the main resonance of the system. -\item A sweep-sine from 10Hz to 400Hz is used (Figure \ref{fig:exc_signal_2_sweep}). -The sweep-sine is is notched around the estimated resonance of the system. -\item A band-limited white noise from 300Hz to 2kHz is used to estimate the high frequency behavior (Figure \ref{fig:exc_signal_3_hf_noise}). -\end{enumerate} - -For all the excitation signals, before the excitation starts, the mean voltage is slowly increased halfway between the minimum voltage (-20V) and the maximum (150V). - -The first measurement is only used to have a first estimation of the dynamics and verify that everything is setup correctly. -The second excitation is done to estimate the dynamics from 10Hz to 350Hz and the third excitation from 350Hz to 2kHz. -The second and third measurements are therefore combined in the frequency domain to form one good estimation of the dynamics from 10Hz up to 2kHz. - -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/exc_signal_1_noise.png} -\caption{\label{fig:exc_signal_1_noise}Low pass filtered white noise. Time domain (left), Frequency domain (right)} -\end{figure} - -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/exc_signal_2_sweep.png} -\caption{\label{fig:exc_signal_2_sweep}Sweep Sine with a decreased amplitude around the resonance of the APA} -\end{figure} - -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/exc_signal_3_hf_noise.png} -\caption{\label{fig:exc_signal_3_hf_noise}Band-pass white noise. Time domain (left), Frequency domain (right)} -\end{figure} -\subsection{First Measurement} -For this first measurement for the first APA, a basic logarithmic sweep is used between 10Hz and 2kHz. - -The data are loaded. -The initial time is set to zero. -The excitation signal is shown in Figure \ref{fig:apa_bench_exc_sweep}. -It is a sweep sine from 10Hz up to 2kHz filtered with a notch centered with the main resonance of the system and a low pass filter. -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/apa_bench_exc_sweep.png} -\caption{\label{fig:apa_bench_exc_sweep}Excitation voltage} -\end{figure} -\subsection{FRF - Setup} -Let's define the sampling time/frequency. -Then we defined a ``Hanning'' windows that will be used for the spectral analysis: -We get the frequency vector that will be the same for all the frequency domain analysis. -\subsection{FRF - Encoder and Interferometer} -In this section, the transfer function from the excitation voltage \(V_a\) to the encoder measured displacement \(d_e\) and interferometer measurement \(d_a\). - -The coherence from \(V_a\) to \(d_e\) and from \(V_a\) to \(d_a\) are computed and shown in Figure \ref{fig:apa_1_coh_dvf}. -They are quite good from 10Hz up to 500Hz. -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/apa_1_coh_dvf.png} -\caption{\label{fig:apa_1_coh_dvf}Coherence for the identification from \(V_a\) to \(d_e\)} -\end{figure} - -The transfer functions are then estimated and shown in Figure \ref{fig:apa_1_frf_dvf}. -It is shown than both the encoder and interferometers are measuring the same dynamics up to \(\approx 700\,Hz\). -Above that, it is possible that there is some flexible elements apart from the APA that is adding resonances into one or the other FRF. - -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/apa_1_frf_dvf.png} -\caption{\label{fig:apa_1_frf_dvf}Obtained transfer functions from \(V_a\) to both \(d_e\) and \(d_a\)} -\end{figure} - -\begin{important} -The transfer functions obtained in Figure \ref{fig:apa_1_frf_dvf} are very close to what was expected: -\begin{itemize} -\item constant gain at low frequency -\item resonance at around 100Hz which corresponds to the APA axial mode -\item no further resonance up until high frequency (\(\approx 700\,Hz\)) at which points several elements of the test bench can induces resonances in the measured FRF +\item measure the dynamics of the APA (from \(V_a\) to \(d_e\) and \(d_a\) in Section \ref{ssec:test_apa_meas_frf_disp}, and from \(V_a\) to \(V_s\) in section \ref{ssec:test_apa_meas_frf_force}) +\item estimate the added damping using Integral Force Feedback (Section \ref{ssec:test_apa_iff_locus}) \end{itemize} -However, it was not expected to observe a ``double resonance'' at around 95Hz (instead of only one resonance). -\end{important} -\subsection{FRF - Force Sensor} -Now the dynamics from excitation voltage \(V_a\) to the force sensor stack voltage \(V_s\) is identified. +These measurements will also be used to tune the model of the APA in Section \ref{sec:test_apa_simscape}. +\section{Hysteresis} +\label{ssec:test_apa_hysteresis} -The coherence is computed and shown in Figure \ref{fig:apa_1_coh_iff} and found very good from 10Hz up to 2kHz. -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/apa_1_coh_iff.png} -\caption{\label{fig:apa_1_coh_iff}Coherence for the identification from \(V_a\) to \(V_s\)} -\end{figure} +As the payload is vertically guided without friction, the hysteresis of the APA can be estimated from the motion of the payload. -The transfer function is estimated and shown in Figure \ref{fig:apa_1_frf_iff}. -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/apa_1_frf_iff.png} -\caption{\label{fig:apa_1_frf_iff}Obtained transfer functions from \(V_a\) to \(V_s\)} -\end{figure} +A quasi static sinusoidal excitation \(V_a\) with an offset of \(65\,V\) (halfway between \(-20\,V\) and \(150\,V\)), and an amplitude varying from \(4\,V\) up to \(80\,V\). -\begin{important} -The obtained dynamics from the excitation voltage \(V_a\) to the measured sensor stack voltage \(V_s\) is corresponding to what was expected: -\begin{itemize} -\item constant gain at low frequency -\item complex conjugate zero and then complex conjugate pole -\item constant gain at high frequency -\end{itemize} -\end{important} -\subsection{Hysteresis} -We here wish to visually see the amount of hysteresis present in the APA. +For each excitation amplitude, the vertical displacement \(d_e\) of the mass is measured and displayed as a function of the applied voltage.. -To do so, a quasi static sinusoidal excitation \(V_a\) at different voltages is used. - -The offset is 65V (halfway between -20V and 150V), and the sin amplitude is ranging from 1V up to 80V (full range). - -For each excitation amplitude, the vertical displacement \(d\) of the mass is measured. - -Then, \(d\) is plotted as a function of \(V_a\) for all the amplitudes. - -We expect to obtained something like the hysteresis shown in Figure \ref{fig:expected_hysteresis}. +The measured displacements as a function of the output voltages are shown in Figure \ref{fig:test_apa_meas_hysteresis}. +It is interesting to see that the hysteresis is increasing with the excitation amplitude. \begin{figure}[htbp] \centering -\includegraphics[scale=1,width=0.8\linewidth]{figs/expected_hysteresis.png} -\caption{\label{fig:expected_hysteresis}Expected Hysteresis \cite{poel10_explor_activ_hard_mount_vibrat}} +\includegraphics[scale=1]{figs/test_apa_meas_hysteresis.png} +\caption{\label{fig:test_apa_meas_hysteresis}Obtained hysteresis curves (displacement as a function of applied voltage) for multiple excitation amplitudes} \end{figure} +\section{Axial stiffness} +\label{ssec:test_apa_stiffness} -The data is loaded. -The excitation voltage amplitudes are: -The excitation voltage and the measured displacement are shown in Figure \ref{fig:hyst_exc_signal_time}. -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/hyst_exc_signal_time.png} -\caption{\label{fig:hyst_exc_signal_time}Excitation voltage and measured displacement} -\end{figure} +In order to estimate the stiffness of the APA, a weight with known mass \(m_a = 6.4\,\text{kg}\) is added on top of the suspended granite and the deflection \(d_e\) is measured using the encoder. -For each amplitude, we only take the last sinus in order to reduce possible transients. -Also, the motion is centered on zero. +The APA stiffness can then be estimated from equation \eqref{eq:test_apa_stiffness}. -The measured displacement at a function of the output voltage are shown in Figure \ref{fig:hyst_results_multi_ampl}. -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/hyst_results_multi_ampl.png} -\caption{\label{fig:hyst_results_multi_ampl}Obtained hysteresis for multiple excitation amplitudes} -\end{figure} - -\begin{important} -From Figure \ref{fig:hyst_results_multi_ampl}, it is quite clear that hysteresis is increasing with the excitation amplitude. -For small excitation amplitudes (\(V_a < 0.4\,V\)) the hysteresis stays reasonably small. - -Also, it is quite interesting to see that no hysteresis is found on the sensor stack voltage when using the same excitation signal. -\end{important} -\subsection{Estimation of the APA axial stiffness} -In order to estimate the stiffness of the APA, a weight with known mass \(m_a\) is added on top of the suspended granite and the deflection \(d_e\) is measured using the encoder. - -The APA stiffness can then be estimated to be: -\begin{equation} - k_{\text{apa}} = \frac{m_a g}{d} +\begin{equation} \label{eq:test_apa_stiffness} + k_{\text{apa}} = \frac{m_a g}{\Delta d_e} \end{equation} -The data is loaded, and the measured displacement is shown in Figure \ref{fig:apa_1_meas_stiffness}. +The measured displacement \(d_e\) as a function of time is shown in Figure \ref{fig:test_apa_meas_stiffness_time}. +It can be seen that there are some drifts in the measured displacement (probably due to piezoelectric creep) and the that displacement does not come back to the initial position after the mass is removed (probably due to piezoelectric hysteresis). +These two effects induce some uncertainties in the measured stiffness. + \begin{figure}[htbp] \centering -\includegraphics[scale=1]{figs/apa_1_meas_stiffness.png} -\caption{\label{fig:apa_1_meas_stiffness}Measured displacement when adding the mass and removing the mass} +\includegraphics[scale=1]{figs/test_apa_meas_stiffness_time.png} +\caption{\label{fig:test_apa_meas_stiffness_time}Measured displacement when adding the mass (at \(t \approx 3\,s\)) and removing the mass(at \(t \approx 13\,s\))} \end{figure} -From Figure \ref{fig:apa_1_meas_stiffness}, it can be seen that there are some drifts that are probably due to some creep. -This will induce some uncertainties in the measured stiffness. +The stiffnesses are computed for all the APA from the two displacements \(d_1\) and \(d_2\) (see Figure \ref{fig:test_apa_meas_stiffness_time}) leading to two stiffness estimations \(k_1\) and \(k_2\). +These estimated stiffnesses are summarized in Table \ref{tab:test_apa_measured_stiffnesses} and are found to be close to the nominal stiffness \(k = 1.8\,N/\mu m\) found in the APA300ML manual. -Here, a mass of 6.4 kg was used: -The stiffness is then computed as follows: -And the stiffness obtained is very close to the one specified in the documentation (\(k = 1.794\,[N/\mu m]\)). -\begin{verbatim} -k = 1.68 [N/um] -\end{verbatim} - - -The stiffness could also be estimated based on the main vertical resonance of the system at \(\omega_z = 2\pi \cdot 94 \,[rad/s]\). -The suspended mass is \(m_{\text{sus}} = 5\,kg\). -And therefore, the axial stiffness of the APA can be estimated to be: -\begin{equation} -k_{\text{APA}} = m_{\text{sus}} \omega_z^2 -\end{equation} - -\begin{verbatim} -k = 1.99 [N/um] -\end{verbatim} - - -The two values are found relatively close to each other. -Anyway, the stiffness of the model will be tuned to match the measured FRF. -\subsection{Stiffness change due to electrical connections} -Changes in the electrical impedance connected to the piezoelectric actuator causes changes in the mechanical compliance (or stiffness) of the piezoelectric actuator. - -In this section is measured the stiffness of the APA whether the piezoelectric actuator is connected to an open circuit or a short circuit (e.g. the output of a voltage amplifier). - -Note here that the resistor in parallel to the sensor stack is present in both cases. - -First, the data are loaded. -And the initial displacement is set to zero. -The measured displacements are shown in Figure \ref{fig:apa_meas_k_time_oc_cc}. -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/apa_meas_k_time_oc_cc.png} -\caption{\label{fig:apa_meas_k_time_oc_cc}Measured displacement} -\end{figure} - -And the stiffness is estimated in both case. -The results are shown in Table \ref{tab:APA_measured_k_oc_cc}. \begin{table}[htbp] -\caption{\label{tab:APA_measured_k_oc_cc}Measured stiffnesses on ``open'' and ``closed'' circuits} +\caption{\label{tab:test_apa_measured_stiffnesses}Measured stiffnesses (in \(N/\mu m\))} \centering -\begin{tabularx}{0.3\linewidth}{cc} +\begin{tabularx}{0.2\linewidth}{ccc} \toprule - & \(k [N/\mu m]\)\\ +APA & \(k_1\) & \(k_2\)\\ \midrule -Not connected & 2.3\\ -Connected & 1.7\\ +1 & 1.68 & 1.9\\ +2 & 1.69 & 1.9\\ +4 & 1.7 & 1.91\\ +5 & 1.7 & 1.93\\ +6 & 1.7 & 1.92\\ +8 & 1.73 & 1.98\\ \bottomrule \end{tabularx} \end{table} -\begin{important} -Clearly, connecting the actuator stacks to the amplified (basically equivalent as to short circuiting them) lowers its stiffness. -\end{important} -\subsection{Effect of the resistor on the IFF Plant} -A resistor \(R \approx 80.6\,k\Omega\) is added in parallel with the sensor stack. -This has the effect to form a high pass filter with the capacitance of the stack. +The stiffness can also be computed using equation \eqref{eq:test_apa_res_freq} by knowing the main vertical resonance frequency \(\omega_z \approx 94\,\text{Hz}\) (estimated by the dynamical measurements shown in section \ref{ssec:test_apa_meas_frf_disp}) and the suspended mass \(m_{\text{sus}} = 5.7\,\text{kg}\). -This is done for two reasons (explained in details \href{../test-bench-force-sensor/test-bench-force-sensor.org}{this document}): +\begin{equation} \label{eq:test_apa_res_freq} +\omega_z = \sqrt{\frac{k}{m_{\text{sus}}}} +\end{equation} + +The obtain stiffness is \(k \approx 2\,N/\mu m\) which is close to the values found in the documentation and by the ``static deflection'' method. + + +However, changes in the electrical impedance connected to the piezoelectric stacks impacts the mechanical compliance (or stiffness) of the piezoelectric stack \cite[chap. 2]{reza06_piezoel_trans_vibrat_contr_dampin}. + +To estimate this effect, the stiffness of the APA if measured using the ``static deflection'' method in two cases: +\begin{itemize} +\item \(k_{\text{os}}\): piezoelectric stacks left unconnected (or connect to the high impedance ADC) +\item \(k_{\text{sc}}\): piezoelectric stacks short circuited (or connected to the voltage amplifier with small output impedance) +\end{itemize} + +The open-circuit stiffness is estimated at \(k_{\text{oc}} \approx 2.3\,N/\mu m\) and the closed-circuit stiffness \(k_{\text{sc}} \approx 1.7\,N/\mu m\). +\section{Dynamics} +\label{ssec:test_apa_meas_dynamics} + +In this section, the dynamics of the system from the excitation voltage \(u\) to encoder measured displacement \(d_e\) and to the force sensor voltage \(V_s\) is identified. + +The obtained transfer functions for the 6 APA between the excitation voltage \(u\) and the encoder displacement \(d_e\) are shown in Figure \ref{fig:test_apa_frf_encoder}. +The obtained transfer functions are close to a mass-spring-damper system. +The following can be observed: +\begin{itemize} +\item A ``stiffness line'' indicating a static gain equal to \(\approx -17\,\mu m/V\). +The minus sign comes from the fact that an increase in voltage stretches the piezoelectric stack that then reduces the height of the APA +\item A lightly damped resonance at \(95\,\text{Hz}\) +\item A ``mass line'' up to \(\approx 800\,\text{Hz}\), above which some resonances appear +\end{itemize} + +\begin{figure}[htbp] +\centering +\includegraphics[scale=1]{figs/test_apa_frf_encoder.png} +\caption{\label{fig:test_apa_frf_encoder}Estimated Frequency Response Function from generated voltage \(u\) to the encoder displacement \(d_e\) for the 6 APA300ML} +\end{figure} + +The dynamics from \(u\) to the measured voltage across the sensor stack \(V_s\) is also identified and shown in Figure \ref{fig:test_apa_frf_force}. + +A lightly damped resonance is observed at \(95\,\text{Hz}\) and a lightly damped anti-resonance at \(41\,\text{Hz}\). +No additional resonances is present up to at least \(2\,\text{kHz}\) indicating at Integral Force Feedback can be applied without stability issues from high frequency flexible modes. + +As illustrated by the Root Locus, the poles of the closed-loop system converges to the zeros of the open-loop plant. +Suppose that a controller with a very high gain is implemented such that the voltage \(V_s\) across the sensor stack is zero. +In that case, because of the very high controller gain, no stress and strain is present on the sensor stack (and on the actuator stacks are well, as they are both in series). +Such closed-loop system would therefore virtually corresponds to a system for which the piezoelectric stacks have been removed and just the mechanical shell is kept. +From this analysis, the axial stiffness of the shell can be estimated to be \(k_{\text{shell}} = 5.7 \cdot (2\pi \cdot 41)^2 = 0.38\,N/\mu m\). +Such reasoning can lead to very interesting insight into the system just from an open-loop identification. + +\begin{figure}[htbp] +\centering +\includegraphics[scale=1]{figs/test_apa_frf_force.png} +\caption{\label{fig:test_apa_frf_force}Estimated Frequency Response Function from generated voltage \(u\) to the sensor stack voltage \(V_s\) for the 6 APA300ML} +\end{figure} + +All the identified dynamics of the six APA300ML (both when looking at the encoder in Figure \ref{fig:test_apa_frf_encoder} and at the force sensor in Figure \ref{fig:test_apa_frf_force}) are almost identical, indicating good manufacturing repeatability for the piezoelectric stacks and the mechanical lever. +\section{Effect of the resistor on the IFF Plant} +\label{ssec:test_apa_resistance_sensor_stack} + +A resistor \(R \approx 80.6\,k\Omega\) is added in parallel with the sensor stack which has the effect to form a high pass filter with the capacitance of the stack. + +As explain before, this is done for two reasons: \begin{enumerate} \item Limit the voltage offset due to the input bias current of the ADC \item Limit the low frequency gain \end{enumerate} -The (low frequency) transfer function from \(V_a\) to \(V_s\) with and without this resistor have been measured. - -We use a very long ``Hanning'' window for the spectral analysis in order to estimate the low frequency behavior. -And we estimate the transfer function from \(V_a\) to \(V_s\) in both cases: -With the following values of the resistor and capacitance, we obtain a first order high pass filter with a crossover frequency equal to: -\begin{verbatim} -f0 = 0.39 [Hz] -\end{verbatim} - - -The transfer function of the corresponding high pass filter is: -Let's compare the transfer function from actuator stack to sensor stack with and without the added resistor in Figure \ref{fig:frf_iff_effect_R}. -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/frf_iff_effect_R.png} -\caption{\label{fig:frf_iff_effect_R}Transfer function from \(V_a\) to \(V_s\) with and without the resistor \(k\)} -\end{figure} - -\begin{important} -The added resistor has indeed the expected effect of forming an high pass filter. -\end{important} -\section{Comparison of all the APA} -\label{sec:meas_all_apa} -The same measurements that was performed in Section \ref{sec:meas_one_apa} are now performed on all the APA and then compared. -\subsection{Axial Stiffnesses - Comparison} -Let's first compare the APA axial stiffnesses. - -The added mass is: -Here are the numbers of the APA that have been measured: -The data are loaded. -The raw measurements are shown in Figure \ref{fig:apa_meas_k_time}. -All the APA seems to have similar stiffness except the APA 7 which show strange behavior. - -\begin{warning} -It is however strange that the displacement \(d_e\) when the mass is removed is higher for the APA 7 than for the other APA. - -It turns out the PD200 amplifier was connected to only one stack, the other stack was open circuited. Therefore, the total axial stiffness of the APA was increased. -\end{warning} +The (low frequency) transfer function from \(u\) to \(V_s\) with and without this resistor have been measured and are compared in Figure \ref{fig:test_apa_effect_resistance}. +It is confirmed that the added resistor as the effect of adding an high pass filter with a cut-off frequency of \(\approx 0.35\,\text{Hz}\). \begin{figure}[htbp] \centering -\includegraphics[scale=1]{figs/apa_meas_k_time.png} -\caption{\label{fig:apa_meas_k_time}Raw measurements for all the APA. A mass of 6.4kg is added at arround 15s and removed at arround 22s} +\includegraphics[scale=1]{figs/test_apa_effect_resistance.png} +\caption{\label{fig:test_apa_effect_resistance}Transfer function from u to \(V_s\) with and without the resistor \(R\) in parallel with the piezoelectric stack used as the force sensor} \end{figure} +\section{Integral Force Feedback} +\label{ssec:test_apa_iff_locus} -The stiffnesses are computed for all the APA and are summarized in Table \ref{tab:APA_measured_k}. +This test bench can also be used to estimate the damping added by the implementation of an Integral Force Feedback strategy. -\begin{table}[htbp] -\caption{\label{tab:APA_measured_k}Measured stiffnesses} -\centering -\begin{tabularx}{0.3\linewidth}{cc} -\toprule -APA Num & \(k [N/\mu m]\)\\ -\midrule -1 & 1.68\\ -2 & 1.69\\ -4 & 1.7\\ -5 & 1.7\\ -6 & 1.7\\ -7 & 1.93\\ -8 & 1.73\\ -\bottomrule -\end{tabularx} -\end{table} +First, the transfer function \eqref{eq:test_apa_iff_manual_fit} is manually tuned to match the identified dynamics from generated voltage \(u\) to the measured sensor stack voltage \(V_s\) in Section \ref{ssec:test_apa_meas_dynamics}. -\begin{important} -The APA300ML manual specifies the nominal stiffness to be \(1.8\,[N/\mu m]\) which is very close to what have been measured. -Only the APA number 7 is a little bit higher, due to the fact that one of the stack was open-circuited instead of short circuited. -\end{important} -\subsection{FRF - Setup} -As the APA7 was not correctly wired, it is ignored: -The identification is performed in three steps: -\begin{enumerate} -\item White noise excitation with small amplitude. -This is used to determine the main resonance of the system. -\item Sweep sine excitation with the amplitude lowered around the resonance. -The sweep sine is from 10Hz to 400Hz. -\item High frequency noise. -The noise is band-passed between 300Hz and 2kHz. -\end{enumerate} +The obtained parameter values are \(\omega_{\textsc{hpf}} = 0.4\, \text{Hz}\), \(\omega_{z} = 42.7\, \text{Hz}\), \(\xi_{z} = 0.4\,\%\), \(\omega_{p} = 95.2\, \text{Hz}\), \(\xi_{p} = 2\,\%\) and \(g_0 = 0.64\). -Then, the result of the second identification is used between 10Hz and 350Hz and the result of the third identification if used between 350Hz and 2kHz. +\begin{equation} \label{eq:test_apa_iff_manual_fit} +G_{\textsc{iff},m}(s) = g_0 \cdot \frac{1 + 2 \xi_z \frac{s}{\omega_z} + \frac{s^2}{\omega_z^2}}{1 + 2 \xi_p \frac{s}{\omega_p} + \frac{s^2}{\omega_p^2}} \cdot \frac{s}{\omega_{\textsc{hpf}} + s} +\end{equation} -The data are loaded for both the second and third identification: -The time is the same for all measurements. -Then we defined a ``Hanning'' windows that will be used for the spectral analysis: -We get the frequency vector that will be the same for all the frequency domain analysis. -\subsection{FRF - Encoder and Interferometer} -In this section, the dynamics from excitation voltage \(V_a\) to encoder measured displacement \(d_e\) is identified. - -We compute the coherence for 2nd and 3rd identification: -The coherence is shown in Figure \ref{fig:apa_frf_dvf_plant_coh}, and it is found that the coherence is good from low frequency up to 700Hz. +The comparison between the identified plant and the manually tuned transfer function is done in Figure \ref{fig:test_apa_iff_plant_comp_manual_fit}. \begin{figure}[htbp] \centering -\includegraphics[scale=1]{figs/apa_frf_dvf_plant_coh.png} -\caption{\label{fig:apa_frf_dvf_plant_coh}Obtained coherence for the plant from \(V_a\) to \(d_e\)} +\includegraphics[scale=1]{figs/test_apa_iff_plant_comp_manual_fit.png} +\caption{\label{fig:test_apa_iff_plant_comp_manual_fit}Identified IFF plant and manually tuned model of the plant (a time delay of \(200\,\mu s\) is added to the model of the plant to better match the identified phase)} \end{figure} +The implemented Integral Force Feedback Controller transfer function is shown in equation \eqref{eq:test_apa_Kiff_formula}. +It contains an high pass filter (cut-off frequency of \(2\,\text{Hz}\)) to limit the low frequency gain, a low pass filter to add integral action above \(20\,\text{Hz}\), a second low pass filter to add robustness to high frequency resonances and a tunable gain \(g\). -Then, the transfer function from the DAC output voltage \(V_a\) to the measured displacement by the encoders is computed: -The obtained transfer functions are shown in Figure \ref{fig:apa_frf_dvf_plant_tf}. -They are all superimposed. +\begin{equation} \label{eq:test_apa_Kiff_formula} +K_{\textsc{iff}}(s) = -10 \cdot g \cdot \frac{s}{s + 2\pi \cdot 2} \cdot \frac{1}{1 + 2\pi \cdot 20} \cdot \frac{1}{s + 2\pi\cdot 2000} +\end{equation} + +To estimate how the dynamics of the APA changes when the Integral Force Feedback controller is implemented, the test bench shown in Figure \ref{fig:test_apa_iff_schematic} is used. +The transfer function from the ``damped'' plant input \(u\prime\) to the encoder displacement \(d_e\) is identified for several IFF controller gains \(g\). \begin{figure}[htbp] \centering -\includegraphics[scale=1]{figs/apa_frf_dvf_plant_tf.png} -\caption{\label{fig:apa_frf_dvf_plant_tf}Estimated FRF for the DVF plant (transfer function from \(V_a\) to the encoder \(d_e\))} +\includegraphics[scale=1]{figs/test_apa_iff_schematic.png} +\caption{\label{fig:test_apa_iff_schematic}Figure caption} \end{figure} -A zoom on the main resonance is shown in Figure \ref{fig:apa_frf_dvf_zoom_res_plant_tf}. -It is clear that the responses around the resonances are well matching for all the APA. - -It is also clear that there is not a single resonance but two resonances, a first one at 95Hz and a second one at 105Hz. - -\begin{question} -Why is there a double resonance at around 94Hz? -\end{question} +The identified dynamics are then fitted by second order transfer functions using the ``Vector Fitting'' toolbox \cite{gustavsen99_ration_approx_frequen_domain_respon}. +The comparison between the identified damped dynamics and the fitted second order transfer functions is done in Figure \ref{fig:test_apa_identified_damped_plants} for different gains \(g\). +It is clear that large amount of damping is added when the gain is increased and that the frequency of the pole is shifted to lower frequencies. \begin{figure}[htbp] \centering -\includegraphics[scale=1]{figs/apa_frf_dvf_zoom_res_plant_tf.png} -\caption{\label{fig:apa_frf_dvf_zoom_res_plant_tf}Estimated FRF for the DVF plant (transfer function from \(V_a\) to the encoder \(d_e\)) - Zoom on the main resonance} +\includegraphics[scale=1]{figs/test_apa_identified_damped_plants.png} +\caption{\label{fig:test_apa_identified_damped_plants}Identified dynamics (solid lines) and fitted transfer functions (dashed lines) from \(u\prime\) to \(d_e\) for different IFF gains} \end{figure} -\subsection{FRF - Force Sensor} -In this section, the dynamics from \(V_a\) to \(V_s\) is identified. -First the coherence is computed and shown in Figure \ref{fig:apa_frf_iff_plant_coh}. -The coherence is very nice from 10Hz to 2kHz. -It is only dropping near a zeros at 40Hz, and near the resonance at 95Hz (the excitation amplitude being lowered). +The evolution of the pole in the complex plane as a function of the controller gain \(g\) (i.e. the ``root locus'') is computed: +\begin{itemize} +\item using the IFF plant model \eqref{eq:test_apa_iff_manual_fit} and the implemented controller \eqref{eq:test_apa_Kiff_formula} +\item from the fitted transfer functions of the damped plants experimentally identified for several controller gains +\end{itemize} + +The two obtained root loci are compared in Figure \ref{fig:test_apa_iff_root_locus} and are in good agreement considering that the damped plants were only fitted using a second order transfer function. \begin{figure}[htbp] \centering -\includegraphics[scale=1]{figs/apa_frf_iff_plant_coh.png} -\caption{\label{fig:apa_frf_iff_plant_coh}Obtained coherence for the IFF plant} +\includegraphics[scale=1]{figs/test_apa_iff_root_locus.png} +\caption{\label{fig:test_apa_iff_root_locus}Root Locus of the APA300ML with Integral Force Feedback - Comparison between the computed root locus from the plant model (black line) and the root locus estimated from the damped plant pole identification (colorful crosses)} \end{figure} - -Then the FRF are estimated and shown in Figure \ref{fig:apa_frf_iff_plant_tf} -\begin{figure}[htbp] -\centering -\includegraphics[scale=1]{figs/apa_frf_iff_plant_tf.png} -\caption{\label{fig:apa_frf_iff_plant_tf}Identified IFF Plant} -\end{figure} -\subsection{Conclusion} +\section{Conclusion} \begin{important} So far, all the measured FRF are showing the dynamical behavior that was expected. \end{important} \chapter{Test Bench APA300ML - Simscape Model} -\label{sec:simscape_bench_apa} +\label{sec:test_apa_simscape} In this section, a simscape model (Figure \ref{fig:model_bench_apa}) of the measurement bench is used to compare the model of the APA with the measured FRF. After the transfer functions are extracted from the model (Section \ref{sec:simscape_bench_apa_first_id}), the comparison of the obtained dynamics with the measured FRF will permit to: \begin{enumerate} \item Estimate the ``actuator constant'' and ``sensor constant'' (Section \ref{sec:simscape_bench_apa_id_constants}) +\item ``Actuator constant'': Gain from the applied voltage \(V_a\) to the generated Force \(F_a\) +\item ``Sensor constant'': Gain from the sensor stack strain \(\delta L\) to the generated voltage \(V_s\) \item Tune the model of the APA to match the measured dynamics (Section \ref{sec:simscape_bench_apa_tune_2dof_model}) \end{enumerate} @@ -996,8 +597,8 @@ The transfer function from excitation voltage \(V_a\) (before the amplification \begin{enumerate} \item the sensor stack voltage \(V_s\) \item the measured displacement by the encoder \(d_e\) -\item the measured displacement by the interferometer \(d_a\) \end{enumerate} + The obtain dynamics are shown in Figure \ref{fig:apa_model_bench_bode_vs} and \ref{fig:apa_model_bench_bode_dl_z}. It can be seen that: \begin{itemize} @@ -1155,6 +756,6 @@ The dynamics is identified using the Simscape model and compared with the measur The tuned 2DoF is very well representing the (axial) dynamics of the APA. \end{important} \chapter{Conclusion} -\label{sec:test_bench_apa_conclusion} +\label{sec:test_apa_conclusion} \printbibliography[heading=bibintoc,title={Bibliography}] \end{document}