Made sure all Matlab scripts are working fine
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@ -126,9 +126,9 @@ Ttot = Rty*Rry*Rrz;
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ustation_dx = Ttot(1,4);
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ustation_dy = Ttot(2,4);
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ustation_dz = Ttot(3,4);
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ustation_ry = atan2( Ttot(1, 3), sqrt(Ttot(1, 1)^2 + Ttot(1, 2)^2));
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ustation_rx = atan2(-Ttot(2, 3)/cos(Ery), Ttot(3, 3)/cos(Ery));
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ustation_rz = atan2(-Ttot(1, 2)/cos(Ery), Ttot(1, 1)/cos(Ery));
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ustation_ry = atan2( Ttot(1, 3), sqrt(Ttot(1, 1)^2 + Ttot(1, 2)^2));
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ustation_rx = atan2(-Ttot(2, 3)/cos(ustation_ry), Ttot(3, 3)/cos(ustation_ry));
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ustation_rz = atan2(-Ttot(1, 2)/cos(ustation_ry), Ttot(1, 1)/cos(ustation_ry));
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%% Verification using the Simscape model
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% All stages are initialized as rigid bodies to avoid any guiding error
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@ -157,6 +157,6 @@ T_sim = [simout.y.R.Data(:,:,end), [simout.y.x.Data(end); simout.y.y.Data(end);
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sim_dx = T_sim(1,4);
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sim_dy = T_sim(2,4);
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sim_dz = T_sim(3,4);
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sim_ry = atan2( T_sim(1, 3), sqrt(T_sim(1, 1)^2 + T_sim(1, 2)^2));
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sim_rx = atan2(-T_sim(2, 3)/cos(Ery), T_sim(3, 3)/cos(Ery));
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sim_rz = atan2(-T_sim(1, 2)/cos(Ery), T_sim(1, 1)/cos(Ery));
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sim_ry = atan2( T_sim(1, 3), sqrt(T_sim(1, 1)^2 + T_sim(1, 2)^2));
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sim_rx = atan2(-T_sim(2, 3)/cos(sim_ry), T_sim(3, 3)/cos(sim_ry));
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sim_rz = atan2(-T_sim(1, 2)/cos(sim_ry), T_sim(1, 1)/cos(sim_ry));
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@ -77,7 +77,7 @@ load('ustation_frf_com.mat', 'frfs_CoM');
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% Initialization of some variables to the figures
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dirs = {'x', 'y', 'z', 'rx', 'ry', 'rz'};
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stages = {'gbot', 'gtop', 'ty', 'ry', 'rz', 'hexa'}
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stages = {'gbot', 'gtop', 'ty', 'ry', 'rz', 'hexa'};
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f = logspace(log10(10), log10(500), 1000);
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%% Spindle - X response
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@ -139,7 +139,7 @@ xlim([-5, 5]); ylim([-0.4, 0.4]);
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delta_ty = (ty_errors.setpoint(end) - ty_errors.setpoint(1))/(length(ty_errors.setpoint) - 1); % [mm]
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ty_vel = 8*1.125; % [mm/s]
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Ts = delta_ty/ty_vel;
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Fs = 1/Ts
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Fs = 1/Ts;
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% Frequency Analysis
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Nfft = floor(length(ty_errors.setpoint)); % Number of frequency points
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@ -259,7 +259,7 @@ yticks([-30, -15, 0, 15, 30]);
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% Search the best angular match
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fun = @(theta)rms((spindle_errors.Dx - (x0 + R*cos(pi/180*spindle_errors.deg+theta(1)))).^2 + (spindle_errors.Dy - (y0 - R*sin(pi/180*spindle_errors.deg+theta(1)))).^2);
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x0 = [0];
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delta_theta = fminsearch(fun, 0)
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delta_theta = fminsearch(fun, 0);
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% Compute the remaining error after removing the best circular fit
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spindle_errors.Dx_err = spindle_errors.Dx - (x0 + R*cos(pi/180*spindle_errors.deg+delta_theta));
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@ -496,6 +496,6 @@ plot(Dw.t, 1e6*Dw.x, 'DisplayName', '$D_{xf}$');
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plot(Dw.t, 1e6*Dw.y, 'DisplayName', '$D_{yf}$');
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plot(Dw.t, 1e6*Dw.z, 'DisplayName', '$D_{zf}$');
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xlabel('Time [s]'); ylabel('Amplitude [$\mu$m]')
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xlim([0, 1]); ylim([-0.15, 0.15])
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xlim([0, 1]); ylim([-0.6, 0.6])
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leg = legend('location', 'southeast', 'FontSize', 8, 'NumColumns', 1);
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leg.ItemTokenSize(1) = 15;
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@ -322,564 +322,6 @@ CLOSED: [2024-11-06 Wed 16:29]
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PoI | Point of interest
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** Backup - Kinematics
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*** Micro-Station DoF table
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#+name: tab:ustation_dof_summary
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#+caption: Summary of the micro-station degrees-of-freedom
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#+attr_latex: :environment tabularx :width \linewidth :align lX
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#+attr_latex: :center t :booktabs t
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| *Stage* | *Degrees of Freedom* |
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|-------------------+-------------------------------------------------------|
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| Translation stage | $D_y = \pm 10\,mm$ |
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| Tilt stage | $R_y = \pm 3\,\text{deg}$ |
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| Spindle | $R_z = 360\,\text{deg}$ |
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| Micro Hexapod | $D_{xyz} = \pm 10\,mm$, $R_{xyz} = \pm 3\,\text{deg}$ |
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*** Stage specifications
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Translation Stage
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| Axial Motion ($y$) | Radial Motion ($y-z$) | Rotation motion ($\theta-z$) |
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|--------------------+-----------------------+------------------------------|
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| $40nm$ repeat | $20nm$ | $< 1.7 \mu rad$ |
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Tilt stage
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| Axial Error ($y$) | Radial Error ($z$) | Tilt error ($R_y$) |
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|-------------------+--------------------+--------------------|
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| $0.5\mu m$ | $10nm$ | $5 \mu rad$ repeat |
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Spindle
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| Radial Error ($x$-$y$) | Vertical Error ($z$) | Rz |
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|------------------------+----------------------+----------------------------|
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| $0.33\mu m$ | $0.07\mu m$ | $5\,\mu \text{rad}$ repeat |
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Micro Hexapod
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| Motion | Stroke | Repetability | MIM | Stiffness |
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|------------------+--------------+----------------+--------------+---------------|
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| $T_{\mu_x}$ | $\pm10mm$ | $\pm1\mu m$ | $0.5\mu m$ | $>12N/\mu m$ |
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| $T_{\mu_y}$ | $\pm10mm$ | $\pm1\mu m$ | $0.5\mu m$ | $>12N/\mu m$ |
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| $T_{\mu_z}$ | $\pm10mm$ | $\pm1\mu m$ | $0.5\mu m$ | $>135N/\mu m$ |
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| $\theta_{\mu_x}$ | $\pm3 deg$ | $\pm5 \mu rad$ | $2.5\mu rad$ | |
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| $\theta_{\mu_y}$ | $\pm3 deg$ | $\pm5 \mu rad$ | $2.5\mu rad$ | |
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| $\theta_{\mu_z}$ | $\pm0.5 deg$ | $\pm5 \mu rad$ | $2.5\mu rad$ | |
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*** Frames
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Let's define the following frames:
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- $\{W\}$ the frame that is *fixed to the granite* and its origin at the theoretical meeting point between the X-ray and the spindle axis.
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- $\{S\}$ the frame *attached to the sample* (in reality attached to the top platform of the nano-hexapod) with its origin at 175mm above the top platform of the nano-hexapod.
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Its origin is $O_S$.
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- $\{T\}$ the theoretical wanted frame that correspond to the wanted pose of the frame $\{S\}$.
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$\{T\}$ is computed from the wanted position of each stage. It is thus theoretical and does not correspond to a real position.
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The origin of $T$ is $O_T$ and is the wanted position of the sample.
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Thus:
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- the *measurement* of the position of the sample corresponds to ${}^W O_S = \begin{bmatrix} {}^WP_{x,m} & {}^WP_{y,m} & {}^WP_{z,m} \end{bmatrix}^T$ in translation and to $\theta_m {}^W\mathbf{s}_m = \theta_m \cdot \begin{bmatrix} {}^Ws_{x,m} & {}^Ws_{y,m} & {}^Ws_{z,m} \end{bmatrix}^T$ in rotations
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- the *wanted position* of the sample expressed w.r.t. the granite is ${}^W O_T = \begin{bmatrix} {}^WP_{x,r} & {}^WP_{y,r} & {}^WP_{z,r} \end{bmatrix}^T$ in translation and to $\theta_r {}^W\mathbf{s}_r = \theta_r \cdot \begin{bmatrix} {}^Ws_{x,r} & {}^Ws_{y,r} & {}^Ws_{z,r} \end{bmatrix}^T$ in rotations
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*** Positioning Error with respect to the Granite
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The wanted position expressed with respect to the granite is ${}^WO_T$ and the measured position with respect to the granite is ${}^WO_S$, thus the *position error* expressed in $\{W\}$ is
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\[ {}^W E = {}^W O_T - {}^W O_S \]
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The same is true for rotations:
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\[ \theta_\epsilon {}^W\mathbf{s}_\epsilon = \theta_r {}^W\mathbf{s}_r - \theta_m {}^W\mathbf{s}_m \]
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#+begin_src matlab
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WPe = WPr - WPm;
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#+end_src
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#+begin_quote
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Now we want to express this error in a frame attached to the *base of the nano-hexapod* with its origin at the same point where the Jacobian of the nano-hexapod is computed (175mm above the top platform + 90mm of total height of the nano-hexapod).
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Or maybe should we want to express this error with respect to the *top platform of the nano-hexapod*?
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We are measuring the position of the top-platform, and we don't know exactly the position of the bottom platform.
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We could compute the position of the bottom platform in two ways:
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- from the encoders of each stage
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- from the measurement of the nano-hexapod top platform + the internal metrology in the nano-hexapod (capacitive sensors e.g)
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A third option is to say that the maximum stroke of the nano-hexapod is so small that the error should no change to much by the change of base.
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#+end_quote
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*** Position Error Expressed in the Nano-Hexapod Frame
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We now want the position error to be expressed in $\{S\}$ (the frame attach to the sample) for control:
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\[ {}^S E = {}^S T_W \cdot {}^W E \]
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Thus we need to compute the homogeneous transformation ${}^ST_W$.
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Fortunately, this homogeneous transformation can be computed from the measurement of the sample position and orientation with respect to the granite.
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#+begin_src matlab
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Trxm = [1 0 0;
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0 cos(Rxm) -sin(Rxm);
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0 sin(Rxm) cos(Rxm)];
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Trym = [ cos(Rym) 0 sin(Rym);
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0 1 0;
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-sin(Rym) 0 cos(Rym)];
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Trzm = [cos(Rzm) -sin(Rzm) 0;
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sin(Rzm) cos(Rzm) 0;
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0 0 1];
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STw = [[ Trym*Trxm*Trzm , [Dxm; Dym; Dzm]]; 0 0 0 1];
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#+end_src
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Translation Error.
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#+begin_src matlab
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SEm = STw * [WPe(1:3); 0];
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SEm = SEm(1:3);
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#+end_src
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Rotation Error.
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#+begin_src matlab
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SEr = STw * [WPe(4:6); 0];
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SEr = SEr(1:3);
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#+end_src
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#+begin_src matlab
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Etot = [SEm ; SEr]
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#+end_src
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*** Another try
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Let's denote:
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- $\{W\}$ the initial fixed frame
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- $\{R\}$ the reference frame corresponding to the wanted pose of the sample
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- $\{M\}$ the frame corresponding to the measured pose of the sample
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We have then computed:
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- ${}^WT_R$
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- ${}^WT_M$
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We have:
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\begin{align}
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{}^MT_R &= {}^MT_W {}^WT_R \\
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&= {}^WT_M^t {}^WT_R
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\end{align}
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#+begin_src matlab
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MTr = STw'*Ttot;
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#+end_src
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Position error:
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#+begin_src matlab
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MTr(1:3, 1:4)*[0; 0; 0; 1]
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#+end_src
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Orientation error:
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#+begin_src matlab
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MTr(1:3, 1:3)
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#+end_src
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*** Measured Position of the Sample with respect to the Granite
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The measurement of the position of the sample using the metrology system gives the position and orientation of the sample with respect to the granite.
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#+begin_src matlab
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% Measurements: Xm, Ym, Zm, Rx, Ry, Rz
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Dxm = 0; % [m]
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Dym = 0; % [m]
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Dzm = 0; % [m]
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Rxm = 0*pi/180; % [rad]
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Rym = 0*pi/180; % [rad]
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Rzm = 180*pi/180; % [rad]
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#+end_src
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Let's compute the corresponding orientation using screw axis.
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#+begin_src matlab
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Trxm = [1 0 0;
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0 cos(Rxm) -sin(Rxm);
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0 sin(Rxm) cos(Rxm)];
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Trym = [ cos(Rym) 0 sin(Rym);
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0 1 0;
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-sin(Rym) 0 cos(Rym)];
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Trzm = [cos(Rzm) -sin(Rzm) 0;
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sin(Rzm) cos(Rzm) 0;
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0 0 1];
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STw = [[ Trym*Trxm*Trzm , [Dxm; Dym; Dzm]]; 0 0 0 1];
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#+end_src
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We then obtain the orientation measurement in the form of screw coordinate $\theta_m ({}^Ws_{x,m},\ {}^Ws_{y,m},\ {}^Ws_{z,m})^T$ where:
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- $\theta_m = \cos^{-1} \frac{\text{Tr}(R) - 1}{2}$
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- ${}^W\mathbf{s}_m$ is the eigen vector of the rotation matrix $R$ corresponding to the eigen value $\lambda = 1$
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#+begin_src matlab
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thetam = acos((trace(STw(1:3, 1:3))-1)/2); % [rad]
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if thetam == 0
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WSm = [0; 0; 0];
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else
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[V, D] = eig(STw(1:3, 1:3));
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WSm = thetam*V(:, abs(diag(D) - 1) < eps(1));
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end
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#+end_src
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#+begin_src matlab
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WPm = [Dxm ; Dym ; Dzm ; WSm];
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#+end_src
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*** Get resonance frequencies
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#+begin_src matlab
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%% Initialize simulation with default parameters (flexible elements)
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initializeGround();
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initializeGranite();
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initializeTy();
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initializeRy();
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initializeRz();
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initializeMicroHexapod();
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initializeReferences();
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initializeDisturbances();
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initializeSimscapeConfiguration();
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initializeLoggingConfiguration();
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#+end_src
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And we identify the dynamics from forces/torques applied on the micro-hexapod top platform to the motion of the micro-hexapod top platform at the same point.
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#+begin_src matlab
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%% Identification of the compliance
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% Input/Output definition
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clear io; io_i = 1;
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io(io_i) = linio([mdl, '/Micro-Station/Micro Hexapod/Flexible/Fm'], 1, 'openinput'); io_i = io_i + 1; % Direct Forces/Torques applied on the micro-hexapod top platform
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io(io_i) = linio([mdl, '/Micro-Station/Micro Hexapod/Flexible/Dm'], 1, 'output'); io_i = io_i + 1; % Absolute displacement of the top platform
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% Run the linearization
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Gm = linearize(mdl, io, 0);
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Gm.InputName = {'Fmx', 'Fmy', 'Fmz', 'Mmx', 'Mmy', 'Mmz'};
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Gm.OutputName = {'Dx', 'Dy', 'Dz', 'Drx', 'Dry', 'Drz'};
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#+end_src
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#+begin_src matlab
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modes_freq = imag(eig(Gm))/2/pi;
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modes_freq = sort(modes_freq(modes_freq>0));
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#+end_src
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#+begin_src matlab :exports results :results value table replace :tangle no :post addhdr(*this*)
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data2orgtable([modes_freq(1:16), [11.9, 18.6, 37.8, 39.1, 56.3, 69.8, 72.5, 84.8, 91.3, 105.5, 106.6, 112.7, 124.2, 145.3, 150.5, 165.4]'], {'1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15', '16'}, {'Mode', 'Simscape', 'Modal analysis'}, ' %.1f ');
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#+end_src
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#+RESULTS:
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| Mode | Simscape | Modal analysis |
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|------+----------+----------------|
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| 1 | 11.7 | 11.9 |
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| 2 | 21.3 | 18.6 |
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| 3 | 26.1 | 37.8 |
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| 4 | 57.5 | 39.1 |
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| 5 | 60.6 | 56.3 |
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| 6 | 73.0 | 69.8 |
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| 7 | 97.9 | 72.5 |
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| 8 | 120.2 | 84.8 |
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| 9 | 126.2 | 91.3 |
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| 10 | 142.4 | 105.5 |
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| 11 | 155.9 | 106.6 |
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| 12 | 178.5 | 112.7 |
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| 13 | 179.3 | 124.2 |
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| 14 | 182.6 | 145.3 |
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| 15 | 223.6 | 150.5 |
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| 16 | 226.4 | 165.4 |
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*** Noise Budget
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<<ssec:ustation_disturbances_results>>
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- [ ] Compare the PSD of the Z relative motion of the sample due to all disturbances
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- [ ] Is it relevant here as it should be more relevant when doing control / with the nano-hexapod, here we just want to make sure that we have a good model!
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From the obtained spectral density of the disturbance sources, we can compute the resulting relative motion of the Hexapod with respect to the granite using the model.
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This is equivalent as doing the inverse that was done in the previous section.
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This is done in order to verify that this is coherent with the measurements.
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The power spectral density of the relative motion is computed below and the result is shown in Figure ref:fig:psd_effect_dist_verif.
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We can see that this is exactly the same as the Figure ref:fig:dist_effect_relative_motion.
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#+begin_src matlab
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psd_gm_d = gm.psd_gm.*abs(squeeze(freqresp(G('Dz', 'Dw')/s, gm.f, 'Hz'))).^2;
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psd_ty_d = tyz.psd_f.*abs(squeeze(freqresp(G('Dz', 'Fdy')/s, tyz.f, 'Hz'))).^2;
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psd_rz_d = rz.psd_f.*abs(squeeze(freqresp(G('Dz', 'Frz')/s, rz.f, 'Hz'))).^2;
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#+end_src
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#+begin_src matlab :exports none
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figure;
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hold on;
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plot(gm.f, sqrt(psd_gm_d), 'DisplayName', 'Ground Motion');
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plot(tyz.f, sqrt(psd_ty_d), 'DisplayName', 'Ty');
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plot(rz.f, sqrt(psd_rz_d), 'DisplayName', 'Rz');
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hold off;
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set(gca, 'xscale', 'log'); set(gca, 'yscale', 'log');
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xlabel('Frequency [Hz]'); ylabel('ASD of the relative motion $\left[\frac{m}{\sqrt{Hz}}\right]$')
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legend('Location', 'southwest');
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xlim([2, 500]);
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#+end_src
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*** Time Domain Disturbances
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Let's initialize the time domain disturbances and load them.
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#+begin_src matlab
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initializeDisturbances();
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dist = load('nass_disturbances.mat');
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#+end_src
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|
||||
The time domain disturbance signals are shown in Figure ref:fig:disturbances_time_domain.
|
||||
|
||||
#+begin_src matlab :exports none
|
||||
figure;
|
||||
|
||||
ax1 = subplot(2, 2, 1);
|
||||
hold on;
|
||||
plot(dist.t, dist.Dwx, 'DisplayName', '$D_{w,x}$')
|
||||
plot(dist.t, dist.Dwy, 'DisplayName', '$D_{w,y}$')
|
||||
plot(dist.t, dist.Dwz, 'DisplayName', '$D_{w,z}$')
|
||||
hold off;
|
||||
xlabel('Time [s]');
|
||||
ylabel('Ground Motion [m]');
|
||||
legend();
|
||||
|
||||
ax2 = subplot(2, 2, 2);
|
||||
hold on;
|
||||
plot(dist.t, dist.Fdy_x, 'DisplayName', '$F_{ty,x}$')
|
||||
hold off;
|
||||
xlabel('Time [s]');
|
||||
ylabel('Ty Forces [N]');
|
||||
legend();
|
||||
|
||||
ax3 = subplot(2, 2, 3);
|
||||
hold on;
|
||||
plot(dist.t, dist.Fdy_z, 'DisplayName', '$F_{ty,z}$')
|
||||
hold off;
|
||||
xlabel('Time [s]');
|
||||
ylabel('Ty Forces [N]');
|
||||
legend();
|
||||
|
||||
ax4 = subplot(2, 2, 4);
|
||||
hold on;
|
||||
plot(dist.t, dist.Frz_z, 'DisplayName', '$F_{rz,z}$')
|
||||
hold off;
|
||||
xlabel('Time [s]');
|
||||
ylabel('Rz Forces [N]');
|
||||
legend();
|
||||
|
||||
linkaxes([ax1,ax2,ax3,ax4], 'x');
|
||||
xlim([0, dist.t(end)]);
|
||||
#+end_src
|
||||
|
||||
*** Time Domain Effect of Disturbances
|
||||
**** Initialization of the Experiment
|
||||
We initialize all the stages with the default parameters.
|
||||
#+begin_src matlab
|
||||
initializeGround();
|
||||
initializeGranite();
|
||||
initializeTy();
|
||||
initializeRy();
|
||||
initializeRz();
|
||||
initializeMicroHexapod();
|
||||
initializeAxisc();
|
||||
initializeMirror();
|
||||
#+end_src
|
||||
|
||||
The nano-hexapod is a piezoelectric hexapod and the sample has a mass of 50kg.
|
||||
#+begin_src matlab
|
||||
initializeNanoHexapod('type', 'rigid');
|
||||
initializeSample('mass', 1);
|
||||
#+end_src
|
||||
|
||||
#+begin_src matlab
|
||||
initializeReferences();
|
||||
initializeController('type', 'open-loop');
|
||||
initializeSimscapeConfiguration('gravity', false);
|
||||
initializeLoggingConfiguration('log', 'all');
|
||||
#+end_src
|
||||
|
||||
#+begin_src matlab
|
||||
load('mat/conf_simulink.mat');
|
||||
set_param(conf_simulink, 'StopTime', '2');
|
||||
#+end_src
|
||||
|
||||
**** Simulations
|
||||
|
||||
No disturbances:
|
||||
#+begin_src matlab
|
||||
initializeDisturbances('enable', false);
|
||||
sim('nass_model');
|
||||
sim_no = simout;
|
||||
#+end_src
|
||||
|
||||
Ground Motion:
|
||||
#+begin_src matlab
|
||||
initializeDisturbances('Fdy_x', false, 'Fdy_z', false, 'Frz_x', false, 'Frz_y', false, 'Frz_z', false);
|
||||
sim('nass_model');
|
||||
sim_gm = simout;
|
||||
#+end_src
|
||||
|
||||
Translation Stage Vibrations:
|
||||
#+begin_src matlab
|
||||
initializeDisturbances('Dwx', false, 'Dwy', false, 'Dwz', false, 'Frz_z', false);
|
||||
sim('nass_model');
|
||||
sim_ty = simout;
|
||||
#+end_src
|
||||
|
||||
Rotation Stage Vibrations:
|
||||
#+begin_src matlab
|
||||
initializeDisturbances('Dwx', false, 'Dwy', false, 'Dwz', false, 'Fdy_x', false, 'Fdy_z', false);
|
||||
sim('nass_model');
|
||||
sim_rz = simout;
|
||||
#+end_src
|
||||
|
||||
**** Comparison
|
||||
Let's now compare the effect of those perturbations on the position error of the sample (Figure ref:fig:effect_disturbances_position_error)
|
||||
|
||||
#+begin_src matlab :exports none
|
||||
figure;
|
||||
ax1 = subplot(2, 3, 1);
|
||||
hold on;
|
||||
plot(sim_no.Em.En.Time, sim_no.Em.En.Data(:, 1))
|
||||
plot(sim_gm.Em.En.Time, sim_gm.Em.En.Data(:, 1))
|
||||
plot(sim_ty.Em.En.Time, sim_ty.Em.En.Data(:, 1))
|
||||
plot(sim_rz.Em.En.Time, sim_rz.Em.En.Data(:, 1))
|
||||
hold off;
|
||||
xlabel('Time [s]');
|
||||
ylabel('Dx [m]');
|
||||
|
||||
ax2 = subplot(2, 3, 2);
|
||||
hold on;
|
||||
plot(sim_no.Em.En.Time, sim_no.Em.En.Data(:, 2))
|
||||
plot(sim_gm.Em.En.Time, sim_gm.Em.En.Data(:, 2))
|
||||
plot(sim_ty.Em.En.Time, sim_ty.Em.En.Data(:, 2))
|
||||
plot(sim_rz.Em.En.Time, sim_rz.Em.En.Data(:, 2))
|
||||
hold off;
|
||||
xlabel('Time [s]');
|
||||
ylabel('Dy [m]');
|
||||
|
||||
ax3 = subplot(2, 3, 3);
|
||||
hold on;
|
||||
plot(sim_no.Em.En.Time, sim_no.Em.En.Data(:, 3))
|
||||
plot(sim_gm.Em.En.Time, sim_gm.Em.En.Data(:, 3))
|
||||
plot(sim_ty.Em.En.Time, sim_ty.Em.En.Data(:, 3))
|
||||
plot(sim_rz.Em.En.Time, sim_rz.Em.En.Data(:, 3))
|
||||
hold off;
|
||||
xlabel('Time [s]');
|
||||
ylabel('Dz [m]');
|
||||
|
||||
ax4 = subplot(2, 3, 4);
|
||||
hold on;
|
||||
plot(sim_no.Em.En.Time, sim_no.Em.En.Data(:, 4))
|
||||
plot(sim_gm.Em.En.Time, sim_gm.Em.En.Data(:, 4))
|
||||
plot(sim_ty.Em.En.Time, sim_ty.Em.En.Data(:, 4))
|
||||
plot(sim_rz.Em.En.Time, sim_rz.Em.En.Data(:, 4))
|
||||
hold off;
|
||||
xlabel('Time [s]');
|
||||
ylabel('Rx [rad]');
|
||||
|
||||
ax5 = subplot(2, 3, 5);
|
||||
hold on;
|
||||
plot(sim_no.Em.En.Time, sim_no.Em.En.Data(:, 5))
|
||||
plot(sim_gm.Em.En.Time, sim_gm.Em.En.Data(:, 5))
|
||||
plot(sim_ty.Em.En.Time, sim_ty.Em.En.Data(:, 5))
|
||||
plot(sim_rz.Em.En.Time, sim_rz.Em.En.Data(:, 5))
|
||||
hold off;
|
||||
xlabel('Time [s]');
|
||||
ylabel('Ry [rad]');
|
||||
|
||||
ax6 = subplot(2, 3, 6);
|
||||
hold on;
|
||||
plot(sim_no.Em.En.Time, sim_no.Em.En.Data(:, 6), 'DisplayName', 'No')
|
||||
plot(sim_gm.Em.En.Time, sim_gm.Em.En.Data(:, 6), 'DisplayName', 'Dw')
|
||||
plot(sim_ty.Em.En.Time, sim_ty.Em.En.Data(:, 6), 'DisplayName', 'Ty')
|
||||
plot(sim_rz.Em.En.Time, sim_rz.Em.En.Data(:, 6), 'DisplayName', 'Rz')
|
||||
hold off;
|
||||
xlabel('Time [s]');
|
||||
ylabel('Rz [rad]');
|
||||
legend();
|
||||
|
||||
linkaxes([ax1,ax2,ax3,ax4,ax5,ax6],'x');
|
||||
#+end_src
|
||||
|
||||
#+header: :tangle no :exports results :results none :noweb yes
|
||||
#+begin_src matlab :var filepath="figs/effect_disturbances_position_error.pdf" :var figsize="full-tall" :post pdf2svg(file=*this*, ext="png")
|
||||
<<plt-matlab>>
|
||||
#+end_src
|
||||
|
||||
#+name: fig:effect_disturbances_position_error
|
||||
#+caption: Effect of Perturbations on the position error ([[./figs/effect_disturbances_position_error.png][png]], [[./figs/effect_disturbances_position_error.pdf][pdf]])
|
||||
[[file:figs/effect_disturbances_position_error.png]]
|
||||
|
||||
|
||||
*** Power Spectral Density of the effect of the disturbances
|
||||
|
||||
#+begin_src matlab
|
||||
figure;
|
||||
hold on;
|
||||
hold off;
|
||||
set(gca, 'xscale', 'log'); set(gca, 'yscale', 'log');
|
||||
xlabel('Frequency [Hz]'); ylabel('ASD $\left[\frac{\mu m}{\sqrt{Hz}}\right]$')
|
||||
#+end_src
|
||||
|
||||
#+begin_src matlab
|
||||
figure;
|
||||
hold on;
|
||||
plot(f_rz, sqrt(pxx_rz_dx), 'DisplayName', '$D_x$')
|
||||
plot(f_rz, sqrt(pxx_rz_dy), 'DisplayName', '$D_y$')
|
||||
plot(f_rz, sqrt(pxx_rz_dz), 'DisplayName', '$D_z$')
|
||||
plot(f_dy, sqrt(pxx_dy_dz))
|
||||
hold off;
|
||||
set(gca, 'xscale', 'log'); set(gca, 'yscale', 'log');
|
||||
xlabel('Frequency [Hz]'); ylabel('ASD $\left[\frac{m}{\sqrt{Hz}}\right]$')
|
||||
xlim([1, 200]);
|
||||
legend('location', 'northeast', 'FontSize', 8, 'NumColumns', 1);
|
||||
#+end_src
|
||||
|
||||
#+begin_src matlab :results none :exports results
|
||||
figure;
|
||||
hold on;
|
||||
plot(f_rz(f_rz>1&f_rz<200), 1e9*sqrt(flip(-cumtrapz(flip(f_rz(f_rz>1&f_rz<200)),flip(pxx_rz_dx(f_rz>1&f_rz<200))))), 'DisplayName', 'Spindle - $D_x$');
|
||||
plot(f_rz(f_rz>1&f_rz<200), 1e9*sqrt(flip(-cumtrapz(flip(f_rz(f_rz>1&f_rz<200)),flip(pxx_rz_dy(f_rz>1&f_rz<200))))), 'DisplayName', 'Spindle - $D_y$');
|
||||
plot(f_rz(f_rz>1&f_rz<200), 1e9*sqrt(flip(-cumtrapz(flip(f_rz(f_rz>1&f_rz<200)),flip(pxx_rz_dz(f_rz>1&f_rz<200))))), 'DisplayName', 'Spindle - $D_z$');
|
||||
plot(f_dy(f_dy>1&f_dy<200), 1e9*sqrt(flip(-cumtrapz(flip(f_dy(f_dy>1&f_dy<200)),flip(pxx_dy_dz(f_dy>1&f_dy<200))))), 'DisplayName', 'Spindle - $D_z$');
|
||||
hold off;
|
||||
set(gca, 'xscale', 'log');
|
||||
set(gca, 'yscale', 'log');
|
||||
xlabel('Frequency [Hz]'); ylabel('CAS [nm RMS]')
|
||||
legend('Location', 'southwest');
|
||||
xlim([1, 200]);
|
||||
#+end_src
|
||||
|
||||
|
||||
#+begin_src matlab
|
||||
gm = load('matlab/mat/dist/psd_gm.mat', 'f', 'psd_gm');
|
||||
rz = load('matlab/mat/dist/pxsp_r.mat', 'f', 'pxsp_r');
|
||||
tyz = load('matlab/mat/dist/pxz_ty_r.mat', 'f', 'pxz_ty_r');
|
||||
tyx = load('matlab/mat/dist/pxe_ty_r.mat', 'f', 'pxe_ty_r');
|
||||
#+end_src
|
||||
|
||||
#+begin_src matlab :exports none
|
||||
gm.f = gm.f(2:end);
|
||||
rz.f = rz.f(2:end);
|
||||
tyz.f = tyz.f(2:end);
|
||||
tyx.f = tyx.f(2:end);
|
||||
|
||||
gm.psd_gm = gm.psd_gm(2:end); % PSD of Ground Motion [m^2/Hz]
|
||||
rz.pxsp_r = rz.pxsp_r(2:end); % PSD of Relative Velocity [(m/s)^2/Hz]
|
||||
tyz.pxz_ty_r = tyz.pxz_ty_r(2:end); % PSD of Relative Velocity [(m/s)^2/Hz]
|
||||
tyx.pxe_ty_r = tyx.pxe_ty_r(2:end); % PSD of Relative Velocity [(m/s)^2/Hz]
|
||||
#+end_src
|
||||
|
||||
Because some 50Hz and harmonics were present in the ground motion measurement, we remove these peaks with the following code:
|
||||
#+begin_src matlab
|
||||
f0s = [50, 100, 150, 200, 250, 350, 450];
|
||||
for f0 = f0s
|
||||
i = find(gm.f > f0-0.5 & gm.f < f0+0.5);
|
||||
gm.psd_gm(i) = linspace(gm.psd_gm(i(1)), gm.psd_gm(i(end)), length(i));
|
||||
end
|
||||
#+end_src
|
||||
|
||||
We now compute the relative velocity between the hexapod and the granite due to ground motion.
|
||||
#+begin_src matlab
|
||||
gm.psd_rv = gm.psd_gm.*abs(squeeze(freqresp(G('Dz', 'Dw'), gm.f, 'Hz'))).^2;
|
||||
#+end_src
|
||||
|
||||
#+begin_src matlab :exports none
|
||||
figure;
|
||||
hold on;
|
||||
plot(gm.f, sqrt(gm.psd_rv), 'DisplayName', 'Ground Motion');
|
||||
plot(tyz.f, sqrt(tyz.pxz_ty_r), 'DisplayName', 'Ty');
|
||||
plot(rz.f, sqrt(rz.pxsp_r), 'DisplayName', 'Rz');
|
||||
hold off;
|
||||
set(gca, 'xscale', 'log'); set(gca, 'yscale', 'log');
|
||||
xlabel('Frequency [Hz]'); ylabel('ASD of the measured velocity $\left[\frac{m/s}{\sqrt{Hz}}\right]$')
|
||||
legend('Location', 'southwest');
|
||||
xlim([2, 500]);
|
||||
#+end_src
|
||||
|
||||
* Introduction :ignore:
|
||||
|
||||
From the start of this work, it became increasingly clear that an accurate micro-station model was necessary.
|
||||
@ -1309,9 +751,9 @@ Ttot = Rty*Rry*Rrz;
|
||||
ustation_dx = Ttot(1,4);
|
||||
ustation_dy = Ttot(2,4);
|
||||
ustation_dz = Ttot(3,4);
|
||||
ustation_ry = atan2( Ttot(1, 3), sqrt(Ttot(1, 1)^2 + Ttot(1, 2)^2));
|
||||
ustation_rx = atan2(-Ttot(2, 3)/cos(Ery), Ttot(3, 3)/cos(Ery));
|
||||
ustation_rz = atan2(-Ttot(1, 2)/cos(Ery), Ttot(1, 1)/cos(Ery));
|
||||
ustation_ry = atan2( Ttot(1, 3), sqrt(Ttot(1, 1)^2 + Ttot(1, 2)^2));
|
||||
ustation_rx = atan2(-Ttot(2, 3)/cos(ustation_ry), Ttot(3, 3)/cos(ustation_ry));
|
||||
ustation_rz = atan2(-Ttot(1, 2)/cos(ustation_ry), Ttot(1, 1)/cos(ustation_ry));
|
||||
|
||||
%% Verification using the Simscape model
|
||||
% All stages are initialized as rigid bodies to avoid any guiding error
|
||||
@ -1340,9 +782,9 @@ T_sim = [simout.y.R.Data(:,:,end), [simout.y.x.Data(end); simout.y.y.Data(end);
|
||||
sim_dx = T_sim(1,4);
|
||||
sim_dy = T_sim(2,4);
|
||||
sim_dz = T_sim(3,4);
|
||||
sim_ry = atan2( T_sim(1, 3), sqrt(T_sim(1, 1)^2 + T_sim(1, 2)^2));
|
||||
sim_rx = atan2(-T_sim(2, 3)/cos(Ery), T_sim(3, 3)/cos(Ery));
|
||||
sim_rz = atan2(-T_sim(1, 2)/cos(Ery), T_sim(1, 1)/cos(Ery));
|
||||
sim_ry = atan2( T_sim(1, 3), sqrt(T_sim(1, 1)^2 + T_sim(1, 2)^2));
|
||||
sim_rx = atan2(-T_sim(2, 3)/cos(sim_ry), T_sim(3, 3)/cos(sim_ry));
|
||||
sim_rz = atan2(-T_sim(1, 2)/cos(sim_ry), T_sim(1, 1)/cos(sim_ry));
|
||||
#+end_src
|
||||
|
||||
* Micro-Station Dynamics
|
||||
@ -1491,7 +933,7 @@ load('ustation_frf_com.mat', 'frfs_CoM');
|
||||
|
||||
% Initialization of some variables to the figures
|
||||
dirs = {'x', 'y', 'z', 'rx', 'ry', 'rz'};
|
||||
stages = {'gbot', 'gtop', 'ty', 'ry', 'rz', 'hexa'}
|
||||
stages = {'gbot', 'gtop', 'ty', 'ry', 'rz', 'hexa'};
|
||||
f = logspace(log10(10), log10(500), 1000);
|
||||
#+end_src
|
||||
|
||||
@ -2104,7 +1546,7 @@ exportFig('figs/ustation_errors_dy_vertical_remove_mean.pdf', 'width', 'half', '
|
||||
delta_ty = (ty_errors.setpoint(end) - ty_errors.setpoint(1))/(length(ty_errors.setpoint) - 1); % [mm]
|
||||
ty_vel = 8*1.125; % [mm/s]
|
||||
Ts = delta_ty/ty_vel;
|
||||
Fs = 1/Ts
|
||||
Fs = 1/Ts;
|
||||
|
||||
% Frequency Analysis
|
||||
Nfft = floor(length(ty_errors.setpoint)); % Number of frequency points
|
||||
@ -2242,7 +1684,7 @@ exportFig('figs/ustation_errors_spindle_tilt.pdf', 'width', 'third', 'height', '
|
||||
% Search the best angular match
|
||||
fun = @(theta)rms((spindle_errors.Dx - (x0 + R*cos(pi/180*spindle_errors.deg+theta(1)))).^2 + (spindle_errors.Dy - (y0 - R*sin(pi/180*spindle_errors.deg+theta(1)))).^2);
|
||||
x0 = [0];
|
||||
delta_theta = fminsearch(fun, 0)
|
||||
delta_theta = fminsearch(fun, 0);
|
||||
|
||||
% Compute the remaining error after removing the best circular fit
|
||||
spindle_errors.Dx_err = spindle_errors.Dx - (x0 + R*cos(pi/180*spindle_errors.deg+delta_theta));
|
||||
@ -2568,7 +2010,7 @@ plot(Dw.t, 1e6*Dw.x, 'DisplayName', '$D_{xf}$');
|
||||
plot(Dw.t, 1e6*Dw.y, 'DisplayName', '$D_{yf}$');
|
||||
plot(Dw.t, 1e6*Dw.z, 'DisplayName', '$D_{zf}$');
|
||||
xlabel('Time [s]'); ylabel('Amplitude [$\mu$m]')
|
||||
xlim([0, 1]); ylim([-0.15, 0.15])
|
||||
xlim([0, 1]); ylim([-0.6, 0.6])
|
||||
leg = legend('location', 'southeast', 'FontSize', 8, 'NumColumns', 1);
|
||||
leg.ItemTokenSize(1) = 15;
|
||||
#+end_src
|
||||
|
Loading…
Reference in New Issue
Block a user