*Advanced Automation [#zc0d6c13]

** &color(green){[lecture #1]}; 2013.9.5 outline of the lecture, review of classical and modern control theory (1/3) [#we254b0e]

- outline of this lecture
-- syllabus
-- map
#ref(map_v1.0.pdf);
-- evaluation
--- mini report #1 ... 10%
--- mini exam #1 ... 10%
--- mini report #2 ... 10%
--- mini exam #2 ... 10%
--- final report ... 60% 

- review

#ref(2013.09.05-1.jpg,left,noimg,whiteboard #1);
#ref(2013.09.05-2.jpg,left,noimg,whiteboard #2);
... missed (derivation of G(s) = 1/(ms^2+cs+k) by Laplace transformation from given equation of motion) 
#ref(2013.09.05-3.jpg,left,noimg,whiteboard #3);
#ref(2013.09.05-4.jpg,left,noimg,whiteboard #4);


** &color(green){[lecture #2]}; 2013.9.12 CACSD introduction with review of classical and modern control theory (2/3) [#wb3e6bee]

+ introduction of Matlab and Simulink
--[[Basic usage of MATLAB and Simulink>/:~kobayasi/easttimor/2009/text/text_fixed.pdf]]
used for 情報処理演習及び考究II/Consideration and Practice of Information Processing II: Advanced Course of MATLAB
//
+ How to define open-loop system
//
++ &color(black,cyan){TF}; 
 s = tf('s');
 G1 = 1 / (s+1);
 G2 = 1 / (s^2 + 0.1*s + 1);
++ &color(black,lightgreen){SSR};
 A = [-0.3, -1; 1, 0];
 B = [1; 0];
 C = [0, 1];
 D = 0;
 G3 = ss(A, B, C, D);
-- Bode plot
 bode(G1, 'b-', G2, 'g', G3, 'r--');
 grid on;
//
+ open-loop stability can be checked by
//
++ &color(black,cyan){poles of TF};
 roots(G2.den{:})
++ &color(black,lightgreen){eigenvalues of A-matrix in SSR};
 eig(G3.a)
++ also by simulation
#ref(mod0912_1.mdl);
//
+ closed-loop stability
//
 L = 1/(s^3+1.5*s^2+1.5*s+1); % example of open-loop system
 roots(L.den{:}) % confirm the open-loop system is stable 
//
++ graphical test by &color(black,yellow){Nyquist stability criterion}; and &color(black,yellow){Bode plot}; with &color(black,yellow){GM};(gain margin) and &color(black,yellow){PM};(phase margin)
 nyquist(L)
//
 bode(L)
++ numerical test by closed-loop system
 clp_den = L.den{:} + L.num{:};
 roots(clp_den)
++ simulation
#ref(mod0912_2.mdl);

 a = 1
 ver
 t = [1 2 3]
 pwd
 ls
 foo
 pwd
 bar
 s = tf('s')
 G1 = 1 / (s+1);
 G2 = 1 / (s^2 + 0.1*s + 1);
 G1
 G2
 A = [-0.3, -1; 1, 0];
 B = [1; 0];
 C = [0, 1];
 D = 0;
 G3 = ss(A, B, C, D);
 G3
 bode(G1, 'b-', G2, 'g', G3, 'r--');
 grid on;
 G2
 G2.den
 G2.den{:}
 roots(G2.den{:})
 G3.a
 eig(G3.a)
 mod0912_1
 L = 1/(s^3+1.5*s^2+1.5*s+1); % example of open-loop system
 roots(L.den{:}) % confirm the open-loop system is stable
 nyquist(L)
 nyquist(L*1.25)
 nyquist(L)
 clp_den = L.den{:} + L.num{:};
 roots(clp_den)
 ex0912_2
 mod0912_2
 L = 1.5*L 

#ref(2013.09.12-1.jpg,left,noimg,whiteboard #1);
#ref(2013.09.12-2.jpg,left,noimg,whiteboard #2);

** &color(green){[lecture #3]}; 2013.9.19 CACSD introduction with review of classical and modern control theory (3/3) [#ubfee4e1]

+ LQR problem
+ ARE and quadratic equation
#ref(J.pdf);
+ (semi)-positive definiteness
+ example
#ref(mod0919.mdl);

 mod0919
 A = [1, 2, 3; 4, 5, 6; 7, 8, 9]
 eig(A)
 B = [1; 1; 1]
 Uc = ctrb(A, B)
 det(Uc)
 B = [1; 0; 0]
 Uc = ctrb(A, B)
 det(Uc)
 help are
 P = are(A, B/R*B', Q)
 Q = eye(3)
 R = 1
 P = are(A, B/R*B', Q)
 P = are(A, B*inv(R)*B', Q)
 P - P'
 eig(P)
 x(0)
 x0 = [1; 1; 1]
 x0'*P*x0
 F = R\B'*P
 C = eye(3)
 D = [0; 0; 0]
 J

#ref(2013.09.19-1.jpg,left,noimg,whiteboard #1);
#ref(2013.09.19-2.jpg,left,noimg,whiteboard #2);
#ref(2013.09.19-3.jpg,left,noimg,whiteboard #3);
#ref(2013.09.19-4.jpg,left,noimg,whiteboard #4);


** &color(green){[lecture #4]}; 2013.9.26 Intro. to robust control theory (H infinity control theory) 1/3 [#edb9111a]
+ Typical design problems
++ robust stabilization
++ &color(black,yellow){performance optimization};
++ robust performance problem (robust stability and performance optimization are simultaneously considered)
//
+ H infinity norm
-- definition
-- example
//
+ H infinity control problem
-- definition
-- application example : reference tracking problem
--- relation to the sensitivity function S(s) (S(s) -> 0 is desired but impossible)
--- given control system
#ref(ex0926_1.m)

--- controller design with H infinity control theory
#ref(ex0926_2.m)

 s = tf('s')
 G = 1/(s+1)
 norm(G, 'inf')
 G = s/(s+1)
 norm(G, 'inf')
 G = 1/(s^2+0.1*s+1)
 bodemag(G)
 norm(G, 'inf')
 bodemag(G, 'b', ss(10.0125), 'r--')
 G = 1/(s^2+0.5*s+1)
 norm(G, 'inf')
 bodemag(G, 'b', ss(2.0656), 'r--')
 ex0926_1
 ex0926_2
 eig(K_hinf)

#ref(2013.09.26-1.jpg,left,noimg,whiteboard #1);
#ref(2013.09.26-2.jpg,left,noimg,whiteboard #2);
#ref(2013.09.26-3.jpg,left,noimg,whiteboard #3);
#ref(2013.09.26-4.jpg,left,noimg,whiteboard #4);

** &color(green){[lecture #5]}; %% 2013.10.3 Intro. to Robust Control Theory (H infinity control theory) 2/3 %% &color(red){&size(20){cancelled};}; [#r0a1de6e]

** &color(green){[lecture #5]}; 2013.10.10 Intro. to Robust Control Theory (H infinity control theory) 2/3 [#cf0799b9]
+ Typical design problems
++ &color(black,yellow){robust stabilization};
++ performance optimization
++ robust performance problem (robust stability and performance optimization are simultaneously considered)
//
+ connection between [H infinity control problem] and [robust stabilization problem]
-- small gain theorem
-- normalized uncertainty \Delta
-- sketch proof ... Nyquist stability criterion
+ How to design robust stabilizing controller with H infinity control problem ?
-- practical example : unstable plant with perturbation
#ref(ex1010_1.m)
-- how to use uncertainty model (multiplicative uncertainty model)
#ref(ex1010_2.m)
-- how to set generalized plant G ?
#ref(ex1010_3.m)
-- simulation
#ref(mod1010.mdl)

 ex1010_1
 ex1010_2
 WT]
 WT
 P0
 P0_jw
 ex1010_3
 mod1010

#ref(2013.10.10-1.jpg,left,noimg,whiteboard #1);
#ref(2013.10.10-2.jpg,left,noimg,whiteboard #2);
#ref(2013.10.10-3.jpg,left,noimg,whiteboard #3);
#ref(2013.10.10-4.jpg,left,noimg,whiteboard #4);

** &color(green){[lecture #6]}; 2013.10.17 Intro. to robust control theory (H infinity control theory) (3/3) [#kfa23202]
+ review
-- robust stabilization ... (1) ||WT T||_inf < 1 (for multiplicative uncertainty)
-- performance optimization ... (2) ||WS S||_inf < gamma -> min
-- &color(black,yellow){mixed sensitivity problem}; ... simultaneous consideration of stability and performance
+ a sufficient condition for (1) and (2) ... (*) property of maximum singular value
+ definition of singular value
+ mini report #1
+ meaning of singular value ... singular value decomposition (SVD)
+ proof of (*)
+ example
#ref(ex1017.m);
//#ref(mod1017.mdl);

 j
 A = [1, j; 0, 2]
 A'
 eig(A'*A)
 sqrt(ans)
 3+sqrt(5)
 sqrt(3+sqrt(5))
 sqrt(3-sqrt(5))
 A
 [U,S,V] = svd(A)
 U'*U
 U*U'
 help svd
 ex1017

#ref(2013.10.17-1.jpg,left,noimg,whiteboard #1);
#ref(2013.10.17-2.jpg,left,noimg,whiteboard #2);
#ref(2013.10.17-3.jpg,left,noimg,whiteboard #3);
... sorry for missing to take photo ... &color(red){&size(20){mini report #1: write by hand; submit at the beginning of the next lecture; You will have a mini exam #1 related to this report on 31st Oct.};};
#ref(2013.10.17-4.jpg,left,noimg,whiteboard #4);
#ref(2013.10.17-5.jpg,left,noimg,whiteboard #5);
#ref(2013.10.17-6.jpg,left,noimg,whiteboard #6);

** &color(green){[lecture #7]}; 2013.10.24 review of SVD, motivation of robust performance &color(red){(robust performance problem 1/3), %%state space representation of generalized plant%%}; [#v3874954]
- review of SVD
#ref(ex1024_1.m);
- motivation of robust performance
#ref(ex1024_2.m);
#ref(ex1024_3.m);
... SSR of generalized plant
#ref(ex1024_4.m);

 ex1024_1
 ex1024_2
 ex1024_3
 ex1024_4

#ref(2013.10.24-1.jpg,left,noimg,whiteboard #1);
#ref(2013.10.24-2.jpg,left,noimg,whiteboard #2);
#ref(2013.10.24-3.jpg,left,noimg,whiteboard #3);
#ref(2013.10.24-4.jpg,left,noimg,whiteboard #4);

** &color(green){[lecture #8]}; 2013.10.31 Robust performance problem (2/3) [#e4893dbc]

+ review of mini report #1
+ review of the limitation of mixed sensitivity problem
+ a solution of conservative design
-- example based on the one given in the last lecture
#ref(ex1031_1.m);
-- a check of the conservativeness
#ref(ex1031_2.m);
+ mini exam #1 
#ref(exam1.pdf);

 %-- 10/31/2013 1:02 PM --%
 A = [j, 0; -j, 0]
 A = [j, 0; -j, 1]
 svd(A)
 sqrt((3+sqrt(5))/2)
 sqrt((3-sqrt(5))/2)
 ex1024_2
 ex1024_3
 ex1024_4
 ex1031_1

#ref(2013.10.31-1.jpg,left,noimg,whiteboard #1);
#ref(2013.10.31-2.jpg,left,noimg,whiteboard #2);
#ref(2013.10.31-3.jpg,left,noimg,whiteboard #3);

** &color(green){[lecture #9]}; 2013.11.14 Robust performance problem (3/3) [#w1002562]

- map
- review of #8
- Q1 and Q2
- ex1031_2.m
- scaled H infinity control problem
#ref(ex1114_1.m);
- mini report #2

 ex1024_2
 ex1024_3
 ex1024_4
 ex1024_5
 ex1031_1
 gam
 ex1024_3
 gam
 ex1031_2
 help lft
 ex1031_2
 ex1031_1
 ex1031_2

#ref(2013.11.14-1.jpg,left,noimg,whiteboard #1);
#ref(2013.11.14-2.jpg,left,noimg,whiteboard #2);
#ref(2013.11.14-3.jpg,left,noimg,whiteboard #3);
#ref(2013.11.14-4.jpg,left,noimg,whiteboard #4);
#ref(2013.11.14-5.jpg,left,noimg,whiteboard #5);

** &color(green){[lecture #10]}; 2013.11.21 Robust performance problem (1/3) (cont.) [#d51591df]

- effect of scaling
- mini report #2
- practical design procedure
- derivation of generalized plant in SSR for mixed sensitivity problem

 ex1024_2
 ex1024_3
 gam
 ex1024_4
 ex1031_1
 gam
 ex1031_2
 ex1114_1
 gam

#ref(2013.11.21-1.jpg,left,noimg,whiteboard #1);
#ref(2013.11.21-2.jpg,left,noimg,whiteboard #2);
#ref(2013.11.21-3.jpg,left,noimg,whiteboard #3);
#ref(2013.11.21-4.jpg,left,noimg,whiteboard #4);
#ref(2013.11.21-5.jpg,left,noimg,whiteboard #5);

// ■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■
&color(black,red){&size(20){#################### the remaining page is under construction ###################};};


** &color(green){[lecture #11]}; 2012.11.22 will be given by Prof. Kimura [#b3bcf006]

** &color(green){[lecture #12]}; 2012.11.29 will be given by Prof. Kimura [#l3bcde04]

** &color(green){[lecture #13]}; 2012.12.6 Robust control design for a practical system (1/3) : Active vibration control of a pendulum using linear motor (loudspeaker) [#ucd0105e] &color(red){some mistakes fixed on 2012.12.13}; [#w0e25ce2]

- Experimental setup
#ref(photo1.jpg,left,noimg,photo1);
#ref(photo2.jpg,left,noimg,photo2);
#ref(photo3.jpg,left,noimg,photo3);
#ref(photo4.jpg,left,noimg,photo4);
#ref(photo5.jpg,left,noimg,photo5);

-- linear motor : FOSTEX &color(red){FW-};208N (corn, edge, and damper are partially removed to decrease damping)
-- PSD(Position Sensitive Detector) : Hamamatsu Photonics Corp. C3683-01
-- Potentio meter : Midori Precisions Model QP-2H
-- PC : Dell Dimension 2400 (Intel Celeron 2.4G, Linux 2.4.22, RTlinux-3.2pre3)
-- D/A : CONTEC DA12-4 (PCI) 12bit, 10us
-- A/D : CONTEC AD12-16 (PCI) 12bit, 10us
-- He-Ne Laser : NEC GLG5230

- Objective for control system design
++ to attenuate vibration due to pendulum oscillation
++ robust stability against modelling error due to non-linear dinamics etc.

- Modelling 
-- frequency response experiment results:
#ref(frdata_amp005.dat);
#ref(frdata_amp010.dat);
#ref(frdata_amp020.dat);
&color(red){due to some change on experimental apparatus, please use following data as frequency response experimental results (2012.12.13)};
#ref(frdata_amp005_1st.dat);
#ref(frdata_amp010_1st.dat);
#ref(frdata_amp020_1st.dat);
#ref(frdata_amp005_2nd.dat);
#ref(frdata_amp005_3rd.dat);
#ref(frdata_amp005_4th.dat);

-- example of m-files &color(red){(the following files have been replaced by modified ones (2012.12.13)};
#ref(freqresp.m)
#ref(nominal.m)
#ref(weight.m);
 >> freqresp
 >> nominal
 >> weight
- Controller design (robust performance problem)
-- example of m-file
#ref(cont.m)
 >> cont
-- design example
#ref(cont.dat)
#ref(cont_order.dat)
#ref(cont.mat)
#ref(result.dat)
#ref(result_no.dat)

-- example of m-file to compare designed controllers
#ref(compare.m)

- report
+design your controller(s) so that the system performance is improved compared with the given example above
+Draw the following figures and explain the difference between two control systems &color(red){(your controller and the example above)};:
++bode diagram of controllers
++gain characteristic of closed-loop systems
++time response of control experiment
+Why is the performance of your system improved(or unfortunately decreased)?
--&size(30){&color(red){due date: 27th(Thu) Dec 17:00};};
--submit your report(pdf or doc) by e-mail to kobayasi@nagaokaut.ac.jp
--You can use Japanese
--maximum controller order is 20  
--submit your cont.dat, cont_order.dat, and cont.mat to kobayasi@nagaokaut.ac.jp &size(30){&color(red){not later than %%21th(Fri)%% 25th(Tue) Dec};};

- program sources for frequency response experiment
#ref(freqresp.h)
#ref(freqresp_module.c)
#ref(freqresp_app.c)
-- format of frdata.dat file
--- 1st column: frequency (Hz)
--- 2nd column: gain
--- 3rd column: phase (deg)
--- 4th column: gain
--- 5th column: phase (deg)
- program sources for control experiment
#ref(hinf.h)
#ref(hinf_module.c)
#ref(hinf_app.c)
-- format of result.dat file
--- 1st column: time (s)
--- 2nd column: PSD output (V)
--- 3rd column: Potentio meter output (V)
--- 4th column: control input (V)
--- 5th column: input disturbance (V)
- configuration of control experiment
-- input disturbance is given as described in hinf_module.c: 
 if(t < 0.1){
    w = DIST_AMP;
 }else{
    w = 0;
 }
 da_conv(V_OFFSET + w, 0); // D/A output for linear motor

 freqresp
 nominal
 help n4sid
 load result.dat
 load result_no.dat
 plot(result(:,1),result(:,3),'r',result_no(:,1),result_no(:,2),'g')
 plot(result(:,1),result(:,3),'r',result_no(:,1),result_no(:,3),'g')

#ref(2012.12.06-1.jpg,left,noimg,whiteboard #1);
#ref(2012.12.06-2.jpg,left,noimg,whiteboard #2);
&color(red){... please use the potentio meter output as the measured output instead the PSD output (2012.12.13)};
#ref(2012.12.06-3.jpg,left,noimg,whiteboard #3);
#ref(2012.12.06-4.jpg,left,noimg,whiteboard #4);


** &color(green){[lecture #14]}; 2012.12.13 Robust control design for a practical system (2/3) [#ke2d6da6]

&size(20){&color(red){IMPOTANT};:due to some change on experimental apparatus, &color(red){please use the potentio meter output as the measured output}; instead of the PSD output. Moreover, some files have been re-uploaded due to this change. See previous links.}; 

-explanation of design example (cont. from the previous lecture)
-preparation of your own controller(s)

 %-- 12/13/2012 12:59 PM --%
 freqresp
 pwd
 freqresp
 nominal
 P0
 weight
 cont
 compare
 load result.dat
 plot(result(:,1),result(:,3));
 load result_no.dat
 plot(result_no(:,1),result_no(:,3),'b',result(:,1),result(:,3),'r');
 plot(result_no(:,1),result_no(:,2),'b',result(:,1),result(:,2),'r');
 plot(result_no(:,1),result_no(:,4),'b',result(:,1),result(:,4),'r');

#ref(2012.12.13-1.jpg,left,noimg,whiteboard #3);

** &color(green){[lecture #15]}; 2012.12.20 Robust control design for a practical system (3/3) [#vb924552]

-preparation of your own controller(s)

#ref(load_frdata.m)

[[participant list2012]]

**related links [#g1a68a2b]
//-東ティモール工学部復興支援/support of rehabilitation for faculty of eng. National University of Timor-Leste
//--[[How to control objects>/:~kobayasi/easttimor/2009/index.html]] to design, to simulate and to experiment control system by using MATLAB/Simulink with an application of Inverted Pendulum
--[[Prof. Kimura's page>http://sessyu.nagaokaut.ac.jp/~kimuralab/index.php?%C0%A9%B8%E6%B9%A9%B3%D8%C6%C3%CF%C0]]

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