Removed unused figures/sections/simulinks

index.org

@@ -30,14 +30,14 @@ In section [[sec:system]], a simple system composed of a spindle and a translati
 The rotation induces some coupling between the actuators and their displacement, and modifies the dynamics of the system.
 This is studied using the equations, and some numerical computations are used to compare the use of voice coil and piezoelectric actuators.
 
+In sections [[sec:iff]] and [[sec:dvf]], the use of Integral Force Feedback and Direct Velocity Feedback is studied for the case of rotating positioning platforms.
+
 Then, in section [[sec:control_strategies]], two different control approach are compared where:
 - the measurement is made in the fixed frame
 - the measurement is made in the rotating frame
 
 In section [[sec:simscape]], the analytical study will be validated using a multi body model of the studied system.
 
-Finally, in section [[sec:control]], the control strategies are implemented using Simulink and Simscape and compared.
-
 * System Description and Analysis
 :PROPERTIES:
 :HEADER-ARGS:matlab+: :tangle matlab/system_numerical_analysis.m
@@ -1998,47 +1998,3 @@ First, we create the closed loop systems. Then, we plot the transfer function fr
   The close-loop performance does not vary a lot with the rotating speed (figure [[fig:perfcomp]]) even tough the open loop system is varying quite a lot (figure [[fig:Guu_uv_ws]]).
 #+end_important
 
-** BKMK Plant Control - MIMO approach
-*** Analysis - SVD
-The singular value decomposition of a MIMO system $G$ is defined as follow:
-\[ G = U \Sigma V^H \]
-
-With:
-- $\Sigma$ is an $2 \times 2$ matrix with 2 non-negative *singular values* $\sigma_i$, arranged in descending order along its main diagonal
-- $U$ is an $2 \times 2$ unitary matrix. The columns vectors of $U$, denoted $u_i$, represent the *output directions* of the plant. They are orthonomal
-- $V$ is an $2 \times 2$ unitary matrix. The columns vectors of $V$, denoted $v_i$, represent the *input directions* of the plant. They are orthonomal
-
-We first look at the evolution of the singular values as a function of frequency (figure [[fig:G_sigma]]).
-
-#+begin_src matlab :exports none
-  freqs = logspace(-2, 1, 1000);
-
-  figure;
-  hold on;
-  for i = 1:length(ws)
-    sv = sigma(Gs_vc{i}, 2*pi*freqs);
-    set(gca,'ColorOrderIndex',i)
-    plot(freqs, sv(1, :), 'DisplayName', sprintf('w = %.0f rpm', ws(i)*60/2/pi));
-    set(gca,'ColorOrderIndex',i)
-    plot(freqs, sv(2, :), '--', 'HandleVisibility', 'off');
-  end
-  hold off;
-  set(gca,'xscale','log'); set(gca,'yscale','log');
-  legend('location', 'southwest');
-#+end_src
-
-#+HEADER: :tangle no :exports results :results none :noweb yes
-#+begin_src matlab :var filepath="figs/G_sigma.pdf" :var figsize="full-tall" :post pdf2svg(file=*this*, ext="png")
-  <<plt-matlab>>
-#+end_src
-
-#+LABEL: fig:G_sigma
-#+CAPTION: Evolution of the singular values with frequency
-[[file:figs/G_sigma.png]]
-
-* Control Implementation
-  <<sec:control>>
-
-* Bibliography                                                      :ignore:
-# bibliographystyle:unsrt
-# bibliography:refs.bib