Reformulation of sentences
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@ -11,7 +11,6 @@
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#+HTML_HEAD: <script src="./js/readtheorg.js"></script>
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#+STARTUP: overview
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#+DATE: 05-2020
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#+LATEX_CLASS: cleanreport
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#+LATEX_CLASS_OPTIONS: [conf, hangsection, secbreak]
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@ -42,9 +41,9 @@ To understand the design challenges of such system, a short introduction to Feed
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The mathematical tools (Power Spectral Density, Noise Budgeting, ...) that will be used throughout this study are also introduced.
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To be able to develop both the nano-hexapod and the control architecture in an optimal way, we need a good estimation of:
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- the micro-station dynamics (Section [[sec:micro_station_dynamics]])
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- the frequency content of the sources of disturbances such as vibrations induced by the micro-station's stages and ground motion (Section [[sec:identification_disturbances]])
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To develop both the nano-hexapod and the control architecture in an optimal way, precise estimation of the following is required:
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- micro-station dynamics (Section [[sec:micro_station_dynamics]])
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- frequency content of the sources of disturbances such as vibrations induced by the micro-station's stages and ground motion (Section [[sec:identification_disturbances]])
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A model of the micro-station is then developed and tuned using the previous estimations (Section [[sec:multi_body_model]]).
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@ -139,13 +138,13 @@ Without the use of feedback (i.e. without the nano-hexapod), the disturbances wi
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\end{equation}
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which is, in the case of the NASS out of the specifications (micro-meter range compare to the required $\approx 10nm$).
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In the next section, we see how the use of the feedback system permits to lower the effect of the disturbances $d$ on the sample motion error.
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In the next section, is explained how the use of the feedback lowers the effect of the disturbances $d$ on the sample motion error.
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*** How does the feedback loop is modifying the system behavior?
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If we write down the position error signal $\epsilon = r - y$ as a function of the reference signal $r$, the disturbances $d$ and the measurement noise $n$ (using the feedback diagram in Figure [[fig:classical_feedback_small]]), we obtain:
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From the feedback diagram in Figure [[fig:classical_feedback_small]], the position error signal $\epsilon = r - y$ can be written as a function of the reference signal $r$, the disturbances $d$ and the measurement noise $n$:
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\[ \epsilon = \frac{1}{1 + GK} r + \frac{GK}{1 + GK} n - \frac{G_d}{1 + GK} d \]
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We usually note:
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It is common to define the following two transfer functions:
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\begin{align}
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S &= \frac{1}{1 + GK} \\
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T &= \frac{GK}{1 + GK}
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@ -158,35 +157,35 @@ And the position error can be rewritten as:
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\end{equation}
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From Eq. eqref:eq:closed_loop_error representing the closed-loop system behavior, we can see that:
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From Eq. eqref:eq:closed_loop_error representing the closed-loop system behavior, it is seen that:
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- the effect of disturbances $d$ on $\epsilon$ is multiplied by a factor $S$ compared to the open-loop case
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- the measurement noise $n$ is injected and multiplied by a factor $T$
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Ideally, we would like to design the controller $K$ such that:
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Ideally, it is desired to design the controller $K$ such that:
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- $|S|$ is small to *reduce the effect of disturbances*
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- $|T|$ is small to *limit the injection of sensor noise*
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*** Trade off: Disturbance Reduction / Noise Injection
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We have from the definition of $S$ and $T$ that:
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From the definition of $S$ and $T$:
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\begin{equation}
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S + T = \frac{1}{1 + GK} + \frac{GK}{1 + GK} = 1
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\end{equation}
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meaning that we cannot have $|S|$ and $|T|$ small at the same time.
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meaning that it is not possible to have $|S|$ and $|T|$ small at the same time.
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There is therefore a *trade-off between the disturbance rejection and the measurement noise filtering*.
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Typical shapes of $|S|$ and $|T|$ as a function of frequency are shown in Figure [[fig:h-infinity-2-blocs-constrains]].
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We can observe that $|S|$ and $|T|$ exhibit different behaviors depending on the frequency band:
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It is shown that $|S|$ and $|T|$ exhibit different behaviors depending on the frequency band:
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*At low frequency* (inside the control bandwidth):
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- $|S|$ can be made small and thus the effect of disturbances is reduced
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- $|T| \approx 1$ and all the sensor noise is transmitted
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*At high frequency* (outside the control bandwidth):
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- $|S| \approx 1$ and the feedback system does not reduce the effect of disturbances
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- $|T|$ is small and thus the sensor noise is filtered
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*Near the crossover frequency* (between the two frequency bands):
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- The effect of disturbances is increased
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- *At low frequency* (inside the control bandwidth):
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- $|S|$ can be made small and thus the effect of disturbances is reduced
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- $|T| \approx 1$ and all the sensor noise is transmitted
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- *At high frequency* (outside the control bandwidth):
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- $|S| \approx 1$ and the feedback system does not reduce the effect of disturbances
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- $|T|$ is small and thus the sensor noise is filtered
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- *Near the crossover frequency* (between the two frequency bands):
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- The effect of disturbances is increased
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#+begin_src latex :file h-infinity-2-blocs-constrains.pdf
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\begin{tikzpicture}
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@ -342,7 +341,7 @@ The Power Spectral Density of the output signal $y$ can be computed using:
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Let's consider a signal $y$ that is the sum of two *uncorrelated* signals $u$ and $v$ (Figure [[fig:psd_sum]]).
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We have that the PSD of $y$ is equal to sum of the PSD and $u$ and the PSD of $v$ (can be easily shown from the definition of the PSD):
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The PSD of $y$ is equal to sum of the PSD and $u$ and the PSD of $v$ (can be easily shown from the definition of the PSD):
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\[ S_{yy} = S_{uu} + S_{vv} \]
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#+begin_src latex :file psd_sum.pdf
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@ -367,24 +366,24 @@ We have that the PSD of $y$ is equal to sum of the PSD and $u$ and the PSD of $v
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Let's consider the Feedback architecture in Figure [[fig:classical_feedback_small]] where the position error $\epsilon$ is equal to:
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\[ \epsilon = S r + T n - G_d S d \]
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If we suppose that the signals $r$, $n$ and $d$ are *uncorrelated* (which is a good approximation in our case), the PSD of $\epsilon$ is:
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Supposing that the signals $r$, $n$ and $d$ are *uncorrelated* (which is a good approximation in our case), the PSD of $\epsilon$ is equal to:
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\[ S_{\epsilon \epsilon}(\omega) = |S(j\omega)|^2 S_{rr}(\omega) + |T(j\omega)|^2 S_{nn}(\omega) + |G_d(j\omega) S(j\omega)|^2 S_{dd}(\omega) \]
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And we can compute the RMS value of the residual motion using:
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And the RMS value of the residual motion can be computed using:
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\begin{align*}
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\epsilon_\text{rms} &= \sqrt{ \int_0^\infty S_{\epsilon\epsilon}(\omega) d\omega} \\
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&= \sqrt{ \int_0^\infty \Big( |S(j\omega)|^2 S_{rr}(\omega) + |T(j\omega)|^2 S_{nn}(\omega) + |G_d(j\omega) S(j\omega)|^2 S_{dd}(\omega) \Big) d\omega }
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\end{align*}
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To estimate the PSD of the position error $\epsilon$ and thus the RMS residual motion (in closed-loop), we need to determine:
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To estimate the PSD of the position error $\epsilon$ and thus the RMS residual motion (in closed-loop), the following needs to be determined:
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- The Power Spectral Densities of the signals affecting the system:
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- The disturbances $S_{dd}$: this will be done in Section [[sec:identification_disturbances]]
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- The sensor noise $S_{nn}$: this can be estimated from the sensor data-sheet
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- The wanted sample's motion $S_{rr}$: this is a deterministic signal that we choose.
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For a simple tomography experiment, we can consider that it is equal to $0$ as we only want to compensate all the sample's vibrations
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- The wanted sample's motion $S_{rr}$: this is a deterministic signal that is chosen by the "user".
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For a simple tomography experiment, the wanted sample's motion can consider to be equal to $0$ (the point of interest should stay on the focus X-ray)
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- The dynamics of the complete system comprising the micro-station and the nano-hexapod: $G$, $G_d$.
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To do so, we need to identify the dynamics of the micro-station (Section [[sec:micro_station_dynamics]]), include this dynamics in a model (Section [[sec:multi_body_model]]) and add a model of the nano-hexapod to the model (Section [[sec:nano_hexapod_design]])
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To do so, the dynamics of the micro-station (Section [[sec:micro_station_dynamics]]) should be identified and then included in a model (Section [[sec:multi_body_model]]). Then a model of the nano-hexapod is merged with the micro-station model (Section [[sec:nano_hexapod_design]])
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- The controller $K$ that will be designed in Section [[sec:robust_control_architecture]]
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* Identification of the Micro-Station Dynamics
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@ -418,8 +417,8 @@ Instead, the model will be tuned using both the modal model and the response mod
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To measure the dynamics of such complicated system, it as been chosen to perform a modal analysis.
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To limit the number of degrees of freedom to be measured, we suppose that in the frequency range of interest (DC-300Hz), each of the positioning stage is behaving as a *solid body*.
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Thus, to fully describe the dynamics of the station, we (only) need to measure 6 degrees of freedom for each positioning stage (that is 36 degrees of freedom for the 6 considered solid bodies).
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To limit the number of degrees of freedom to be measured, it is supposed that in the frequency range of interest (DC-300Hz), each of the positioning stage is behaving as a *solid body*.
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Thus, to fully describe the dynamics of the station, only 6 degrees of freedom for each positioning stage (that is 36 degrees of freedom for the 6 considered solid bodies) should be measured.
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In order to perform the modal analysis, the following devices were used:
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@ -467,9 +466,10 @@ Example of the obtained micro-station's mode shapes are shown in Figures [[fig:m
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[[file:figs/mode6.gif]]
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We then reduce the number of degrees of freedom from 69 (23 accelerometers with each 3DOF) to 36 (6 solid bodies with 6 DOF).
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The number of degrees of freedom is then reduced from 69 (23 accelerometers with each 3DOF) down to 36 (6 solid bodies with 6 DOF).
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From the reduced transfer function matrix, we can re-synthesize the response at the 69 measured degrees of freedom and we find that we have an exact match.
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From the reduced transfer function matrix, the responses at the 69 measured degrees of freedom are re-synthesized.
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The original measurements and the synthesized one are compared and found to match.
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#+begin_important
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This confirms the fact that the stages are indeed behaving as a solid body in the frequency band of interest.
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@ -545,7 +545,7 @@ Complete reports on these measurements are accessible [[https://tdehaeze.github.
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<<sec:stage_vibration_motion>>
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*** Introduction :ignore:
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We consider here the vibrations induced by *scans of the translation stage* and *rotation of the spindle*.
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In this section, the vibrations induced by *scans of the translation stage* and *rotation of the spindle* and studied.
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Details reports are accessible [[https://tdehaeze.github.io/meas-analysis/disturbance-ty/index.html][here]] for the translation stage and [[https://tdehaeze.github.io/meas-analysis/disturbance-sr-rz/index.html][here]] for the spindle/slip-ring.
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@ -567,7 +567,7 @@ A geophone is fixed at the location of the sample and the motion is measured:
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The obtained Power Spectral Densities of the sample's absolute velocity are shown in Figure [[fig:sr_sp_psd_sample_compare]].
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We can see that when using the Slip-ring motor to rotate the sample, only a little increase of the motion is observed above 100Hz.
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It can be seen that when using the Slip-ring motor to rotate the sample, only a little increase of the motion is observed above 100Hz.
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However, when rotating with the Spindle (normal functioning mode):
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- a very sharp peak at 23Hz is observed.
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@ -611,7 +611,7 @@ The ASD contains any peaks starting from 1Hz showing the large spectral content
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A smoother motion for the translation stage (such as a sinus motion, of a filtered triangular signal) could help reducing much of the vibrations.
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The goal is to inject no motion outside the control bandwidth.
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We should also note that away from the rapid change of velocity, the sample's vibrations are much reduced.
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It should be noted that away from the rapid change of velocity, the sample's vibrations are much reduced.
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Thus, if the detector is only used in between the triangular peaks, the vibrations are expected to be much lower than those estimated.
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#+end_important
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@ -622,11 +622,11 @@ The ASD contains any peaks starting from 1Hz showing the large spectral content
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** Open Loop noise budgeting
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<<sec:open_loop_noise_budget>>
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We can now compare the effect of all the disturbance sources on the position error (relative motion of the sample with respect to the granite).
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The effect of all the disturbance sources on the position error (relative motion of the sample with respect to the granite) are now compared.
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The Power Spectral Density of the motion error due to the ground motion, translation stage scans and spindle rotation are shown in Figure [[fig:dist_effect_relative_motion]].
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We can see that the ground motion is quite small compare to the translation stage and spindle induced motions.
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It can be seen that the ground motion is quite small compare to the translation stage and spindle induced motions.
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#+name: fig:dist_effect_relative_motion
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#+caption: Amplitude Spectral Density fo the motion error due to disturbances
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@ -709,7 +709,7 @@ The comparison of three of the Frequency Response Functions are shown in Figure
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Most of the other measured FRFs and identified transfer functions from the multi-body model have the same level of matching.
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We believe that the model is representing the micro-station dynamics with sufficient precision for the current analysis.
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We believe that the model is representing the micro-station dynamics sufficient well for the current analysis.
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#+name: fig:identification_comp_top_stages
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#+caption: Frequency Response function from Hammer force in the X,Y and Z directions to the X,Y and Z displacements of the micro-hexapod's top platform. The measurements are shown in blue and the Model in red.
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@ -724,7 +724,7 @@ Now that the multi-body model dynamics as been tuned, the following elements are
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- Disturbances such as ground motion and stage's vibrations
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Then, using the model, we can
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Then, using the model, it is possible to:
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- perform simulation of experiments in presence of disturbances
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- measure the motion of the solid-bodies
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- identify the dynamics from inputs (forces, imposed displacement) to outputs (measured motion, force sensor, etc.) which will be useful for the nano-hexapod design and the control synthesis
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@ -814,7 +814,7 @@ As explain before, the nano-hexapod properties (mass, stiffness, legs' orientati
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- the effect of disturbances
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- the plant dynamics
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Thus, we here wish to find the optimal nano-hexapod properties such that:
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The objective is here to find the optimal nano-hexapod properties such that:
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- the effect of disturbances is minimized (Section [[sec:optimal_stiff_dist]])
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- the plant uncertainty due to a change of payload mass and experimental conditions is minimized (Section [[sec:optimal_stiff_plant]])
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- the plant has nice dynamical properties for control (Section [[sec:nano_hexapod_architecture]])
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@ -912,9 +912,9 @@ What is more important than comparing the sensitivity to disturbances, is to com
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This is the *dynamic noise budgeting*.
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From the Power Spectral Density of all the sources of disturbances identified in Section [[sec:identification_disturbances]], we compute what would be the Power Spectral Density of the vertical motion error for all the considered nano-hexapod stiffnesses (Figure [[fig:opt_stiff_psd_dz_tot]]).
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From the Power Spectral Density of all the sources of disturbances identified in Section [[sec:identification_disturbances]] is computed the Power Spectral Density of the vertical motion error for all the considered nano-hexapod stiffnesses (Figure [[fig:opt_stiff_psd_dz_tot]]).
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We can see that the most important change is in the frequency range 30Hz to 300Hz where a stiffness smaller than $10^5\,[N/m]$ greatly reduces the sample's vibrations.
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It can be seen that the most important change is in the frequency range 30Hz to 300Hz where a stiffness smaller than $10^5\,[N/m]$ greatly reduces the sample's vibrations.
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#+name: fig:opt_stiff_psd_dz_tot
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#+caption: Amplitude Spectral Density of the Sample vertical position error due to Vertical vibration of the Spindle for multiple nano-hexapod stiffnesses
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@ -926,7 +926,7 @@ We can see that the most important change is in the frequency range 30Hz to 300H
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:END:
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#+begin_important
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If we look at the Cumulative amplitude spectrum of the vertical error motion in Figure [[fig:opt_stiff_cas_dz_tot]], we can observe that a soft hexapod ($k < 10^5 - 10^6\,[N/m]$) helps reducing the high frequency disturbances, and thus a smaller control bandwidth will be required to obtain the wanted performance.
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It can be observe on the Cumulative amplitude spectrum of the vertical error motion in Figure [[fig:opt_stiff_cas_dz_tot]], that a soft hexapod ($k < 10^5 - 10^6\,[N/m]$) helps reducing the high frequency disturbances, and thus a smaller control bandwidth will be required to obtain the wanted performance.
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#+end_important
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#+name: fig:opt_stiff_cas_dz_tot
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@ -938,7 +938,7 @@ If we look at the Cumulative amplitude spectrum of the vertical error motion in
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*** Introduction :ignore:
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One of the most important design goal is to obtain a system that is *robust* to all changes in the system.
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Therefore, we have to identify all changes that might occurs in the system and choose the nano-hexapod stiffness such that the uncertainty to these changes is minimized.
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Therefore, all changes that might occur in the system must be identified and the nano-hexapod stiffness that minimizes the uncertainties to these changes should be determined.
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The uncertainty in the system can be caused by:
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- A change in the *Support's compliance* (complete analysis [[https://tdehaeze.github.io/nass-simscape/uncertainty_support.html][here]]): if the micro-station dynamics is changing due to the change of mechanical parts or just because of aging effects, the feedback system should remains stable and the obtained performance should not change
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@ -949,8 +949,8 @@ Because of the trade-off between robustness and performance, *the bigger the pla
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In the next sections, the effect the considered changes on the *plant dynamics* is quantified and conclusions are drawn on the optimal stiffness for robustness properties.
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In the following study, when we refer to /plant dynamics/, this means the dynamics from forces applied by the nano-hexapod to the measured sample's position by the metrology.
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We will only compare the plant dynamics as it is the most important dynamics for robustness and performance properties.
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In the following study, when it is referred to /plant dynamics/, it means the dynamics from forces applied by the nano-hexapod to the measured sample's displacement by the metrology.
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Only the plant dynamics will be compared as it is the most important dynamics for robustness and performance properties.
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However, the dynamics from forces to sensors located in the nano-hexapod legs, such as force and relative motion sensors, have also been considered in a separate study.
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*** Effect of Payload
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@ -981,7 +981,7 @@ As the maximum payload's mass is $50\,kg$, this may however not be practical, an
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In Figure [[fig:opt_stiffness_payload_freq_fz_dz]] is shown the effect of a change of payload dynamics.
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The mass of the payload is fixed and its resonance frequency is changing from 50Hz to 500Hz.
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We can see (more easily for the soft nano-hexapod), that resonance of the payload produces an anti-resonance for the considered dynamics.
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It can be seen (more easily for the soft nano-hexapod), that resonance of the payload produces an anti-resonance for the considered dynamics.
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#+name: fig:opt_stiffness_payload_freq_fz_dz
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#+caption: Dynamics from $\mathcal{F}_z$ to $\mathcal{X}_z$ for varying payload resonance frequency, both for a soft nano-hexapod and a stiff nano-hexapod
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@ -996,7 +996,7 @@ For nano-hexapod stiffnesses below $10^6\,[N/m]$:
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For nano-hexapod stiffnesses above $10^7\,[N/m]$:
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- the dynamics is unchanged until the first resonance which is around 25Hz-35Hz
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- above that frequency, the change of dynamics is quite chaotic (we will see in the next section that this is due to the micro-station dynamics) and it would be difficult to have a controller with high bandwidth which is robust to such change of dynamics
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- above that frequency, the change of dynamics is quite chaotic (which this is due to the micro-station dynamics as shown in the next section) and it would be difficult to have a controller with high bandwidth which is robust to such change of dynamics
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#+name: fig:opt_stiffness_payload_impedance_all_fz_dz
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#+caption: Dynamics from $\mathcal{F}_z$ to $\mathcal{X}_z$ for varying payload dynamics, both for a soft nano-hexapod and a stiff nano-hexapod
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@ -1204,7 +1204,7 @@ with:
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- $\bm{\tau} = [\tau_1, \tau_2, \cdots, \tau_6]^T$: vector of actuator forces applied in each strut
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- $\bm{\mathcal{F}} = [\bm{f}, \bm{n}]^T$: external force/torque action on the mobile platform
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And thus *the Jacobian matrix can be used to compute the forces that should be applied on each leg from forces and torques that we want to apply on the nano-hexapod's top platform*.
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And thus *the Jacobian matrix can be used to compute the forces that should be applied by the Stewart platform's legs from the wanted total forces/torques that is to be applied to the sample*.
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Linear transformations in Eq. eqref:eq:jacobian_L and eqref:eq:jacobian_F will be widely in the developed control architectures in Section [[sec:robust_control_architecture]].
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@ -1224,7 +1224,7 @@ An example of the mobility considering only pure translations is shown in Figure
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From a wanted mobility and a specific geometry, the required actuator stroke can be estimated.
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Suppose we want the following mobility:
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Suppose the following specifications on the mobility:
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- x, y and z translations up to $50\,\mu m$
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- x and y rotation up to $30\,\mu rad$
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- no z rotation
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@ -1246,7 +1246,7 @@ The stiffness of the actuator $k_i$ links the applied (constant) actuator force
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\begin{equation*}
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\tau_i = k_i \delta l_i, \quad i = 1,\ \dots,\ 6
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\end{equation*}
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If we combine these 6 relations:
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Combining these 6 relations:
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\begin{equation*}
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\bm{\tau} = \mathcal{K} \delta \bm{\mathcal{L}} \quad \mathcal{K} = \text{diag}\left[ k_1,\ \dots,\ k_6 \right]
|
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\end{equation*}
|
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@ -1397,13 +1397,17 @@ For instance, the flexible joint used for the ID16 nano-hexapod have the followi
|
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In Section [[sec:optimal_stiff_dist]], it has been concluded that a nano-hexapod stiffness below $10^5-10^6\,[N/m]$ helps reducing the high frequency vibrations induced by all sources of disturbances considered.
|
||||
As the high frequency vibrations are the most difficult to compensate for when using feedback control, a soft hexapod will most certainly helps improving the performances.
|
||||
|
||||
In Section [[sec:optimal_stiff_plant]], we concluded that a nano-hexapod leg stiffness in the range $10^5 - 10^6\,[N/m]$ is a good compromise between the uncertainty induced by the micro-station dynamics and by the rotating speed.
|
||||
|
||||
In Section [[sec:optimal_stiff_plant]], it has been concluded that a nano-hexapod leg stiffness in the range $10^5 - 10^6\,[N/m]$ is a good compromise between the uncertainty induced by the micro-station dynamics and by the rotating speed.
|
||||
Provided that the samples used have a first mode that is sufficiently high in frequency, the total plant dynamic uncertainty should be manageable by the control.
|
||||
|
||||
|
||||
Thus, a leg's stiffness of $10^5\,[N/m]$ will be used in Section [[sec:robust_control_architecture]] to develop the robust control architecture and to perform simulations.
|
||||
|
||||
|
||||
A more detailed study of the determination of the optimal stiffness based on all the effects is available [[https://tdehaeze.github.io/nass-simscape/uncertainty_optimal_stiffness.html][here]].
|
||||
|
||||
|
||||
Finally, in section [[sec:nano_hexapod_architecture]] some insights on the wanted nano-hexapod geometry are given.
|
||||
#+end_important
|
||||
|
||||
@ -1855,7 +1859,7 @@ Several observations can be made:
|
||||
- The sample's vibrations are reduced within the control bandwidth as was expected
|
||||
- The obtained performances for all the three considered masses are very similar.
|
||||
This is an indication of the good system's robustness
|
||||
- From the Cumulative Amplitude Spectrum (Figure [[fig:opt_stiff_hac_dvf_L_cas_disp_error]]), we see that Z motion is reduced down to $\approx 30\,nm\,[rms]$ and the Y motion down to $\approx 25\,nm\,[rms]$
|
||||
- From the Cumulative Amplitude Spectrum (Figure [[fig:opt_stiff_hac_dvf_L_cas_disp_error]]), it can be seen that Z motion is reduced down to $\approx 30\,nm\,[rms]$ and the Y motion down to $\approx 25\,nm\,[rms]$
|
||||
- An increase in the rotational vibrations is observed.
|
||||
This is due to the fact that:
|
||||
1. no perturbations inducing rotations were included in the simulation and thus the rotational vibrations are very small
|
||||
@ -1880,7 +1884,7 @@ Several observations can be made:
|
||||
The time domain sample's vibrations are shown in Figure [[fig:opt_stiff_hac_dvf_L_pos_error]].
|
||||
The use of the nano-hexapod combined with the HAC-LAC architecture is shown to considerably reduce the sample's vibrations.
|
||||
|
||||
An animation of the experiment is shown in Figure [[fig:closed_loop_sim_zoom]] and we can see that the actual sample's position is more closely following the ideal position compared to the simulation of the micro-station alone in Figure [[fig:open_loop_sim_zoom]] (same scale was used for both animations).
|
||||
An animation of the experiment is shown in Figure [[fig:closed_loop_sim_zoom]] and it can be seen that the actual sample's position is more closely following the ideal position compared to the simulation of the micro-station alone in Figure [[fig:open_loop_sim_zoom]] (same scale was used for both animations).
|
||||
|
||||
#+name: fig:opt_stiff_hac_dvf_L_pos_error
|
||||
#+caption: Position Error of the sample during a tomography experiment when no control is applied and with the HAC-DVF control architecture
|
||||
@ -2036,7 +2040,7 @@ Table summarizing the nano-hexapod wanted characteristics:
|
||||
- Static positioning errors of the stages
|
||||
- Maximum tracking errors of the stages (mainly translation stage and tilt stage).
|
||||
This is probably more difficult to obtain.
|
||||
However, by limiting the acceleration of these stages, we may limit the dynamic tracking errors to acceptable levels
|
||||
However, by limiting the acceleration of these stages, we may limit the dynamic tracking errors to acceptable levels
|
||||
- Sensors to be included
|
||||
|
||||
#+name: fig:nano_hexapod_size
|
||||
|
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Reference in New Issue
Block a user