[[授業]]

*Advanced Automation [#ye2d4ebb]

** &color(green){[lecture #1]}; 2015.9.3 outline of the lecture, review of classical and modern control theory (1/3) [#bdb8b1f6]

- outline of this lecture 
-- syllabus
-- evaluation
--- mini report #1 ... 10%
--- mini exam #1 ... 10%
--- mini report #2 ... 10%
--- mini exam #2 ... 10%
--- final report ... 60% 
-- [[schedule2015]] (tentative)
-- map
#ref(map_v1.0_review.pdf);

- review : stabilization of 1st-order unstable plant by classical and modern control theory 
-- transfer function
-- differential equation
-- eigenvalue and pole
-- ...

 %-- 9/3/2015 2:09 PM --%
 s = tf('s')
 Ptf = 1/(s+1)
 pole(Ptf)
 impulse(Ptf)
 Pss = ss(Ptf)
 initial(Pss, 1)
 initial(Pss, 2)

#ref(2015.09.03-1.jpg,left,noimg,whiteboard #1);
#ref(2015.09.03-2.jpg,left,noimg,whiteboard #2);
#ref(2015.09.03-3.jpg,left,noimg,whiteboard #3);
#ref(2015.09.03-4.jpg,left,noimg,whiteboard #4);

&ref(ex0902.m);


** &color(green){[lecture #2]}; 2015.9.10 review of classical and modern control theory (2/3) with introduction of Matlab/Simulink [#x66b415e]

+ introduction of Matlab and Simulink
&ref(text_fixed.pdf); Basic usage of MATLAB and Simulink used for 情報処理演習及び考究II/Consideration and Practice of Information Processing II: Advanced Course of MATLAB
-- interactive system (no compilation, no variable difinition)
-- m file
//
+ system representation: Transfer Function(TF) / State-Space Representation (SSR)
//
-- example: mass-spring-damper system
-- difinition of SSR
-- from SSR to TF
-- from TF to SSR: controllable canonical form
+ open-loop characteristic
-- open-loop stability: poles and eigenvalues
-- Bode plot and frequency response &ref(ex0910_1.m); &ref(mod0910_1.mdl);
--- cut off frequency; DC gain; -40dB/dec; variation of c
--- relation between P(jw) and steady-state response
+ closed-loop stability
-- Nyquist stability criterion (for L(s):stable)
-- Nyquist plot &ref(ex0910_2.m); &ref(mod0910_2.mdl);
--- Gain Margin(GM); Phase Margin(PM)

 %-- 9/10/2015 1:55 PM --%
 ex0910_1
 P
 P.den
 P.den{:}
 P.num{:}
 ex0910_1
 ex0910_2

#ref(2015.09.10-1.jpg,left,noimg,whiteboard #1);
#ref(2015.09.10-2.jpg,left,noimg,whiteboard #2);
#ref(2015.09.10-3.jpg,left,noimg,whiteboard #3);
#ref(2015.09.10-4.jpg,left,noimg,whiteboard #4);

** &color(green){[]}; 2015.9.17 cancelled [#w7af2c97]

** &color(green){[]}; 2015.9.25 no lecture (lectures for Monday are given) [#ne6e400c]


** &color(green){[lecture #3]}; 2015.10.1 review of classical and modern control theory (3/3) [#b83a9a65]

+ LQR problem
-- controllability
-- cost function J >= 0
-- (semi)-positive definiteness
+ solution of LQR problem
-- ARE and quadratic equation
-- closed loop stability ... Lyapunov criterion
-- Jmin
&ref(lqr.pdf); ≒ &ref(proof4.pdf); (from B3「動的システムの解析と制御」)
+ example
&ref(mod1001.mdl);
 A = [1, 2; 0, -1]; % unstable plant
 B = [0; 1];
 Uc = ctrb(A,B);
 det(Uc) % should be nonzero
 C = eye(2); % dummy
 D = zeros(2,1); % dummy
 F = [0, 0]; % without control
 x0 = [1; 1]; % initial state
 Q = eye(2);
 R = 1;
 P = are(A, B/R*B', Q);
 eig(P) % should be positive
 F = R\B'*P;
 x0'*P*x0

 %-- 10/1/2015 2:08 PM --%
 mod1001
 A = [1, 2; 0, -1]; % unstable plant
 B = [0; 1];
 Uc = ctrb(A,B);
 A
 B
 Uc
 det(Uc)
 C = eye(2); % dummy
 D = zeros(2,1); % dummy
 F = [0, 0]; % without control
 x0 = [1; 1]; % initial state
 Q = eye(2);
 R = 1;
 F
 P = are(A, B/R*B', Q);
 P
 eig(P)
 F = R\B'*P;
 F
 J
 x0
 x0'*P*x0
 A-B*F
 eig(A-B*F)

#ref(2015.10.01-1.jpg,left,noimg,whiteboard #1);
#ref(2015.10.01-2.jpg,left,noimg,whiteboard #2);
#ref(2015.10.01-3.jpg,left,noimg,whiteboard #3);
... I'm sorry but all of equations are in the pdf file.
#ref(2015.10.01-4.jpg,left,noimg,whiteboard #4);
#ref(2015.10.01-5.jpg,left,noimg,whiteboard #5);

** &color(green){[lecture #4]}; 2015.10.8 relation between LQR and H infinity control problem (1/2) [#d821c8a6]

- GOAL: to learn difference in concepts between LQR problem and H infinity control problem
- review of LQR problem and the simple example
+ an equivalent problem
+ a simple example of state-feedback H infinity control problem
+ definition of H infinity norm (SISO)
 s = tf('s');
 P1 = 1/(s+1);
 bode(P1);
 norm(P1, 'inf')
 P2 = 1/(s^2 + 0.1*s + 1);
 bode(P2);
 norm(P2, 'inf')
+ definition of H infinity norm (SIMO)
+ solve the problem by hand
+ solve the problem by tool(hinfsyn)
&ref(ex1008.m);

 %-- 10/8/2015 1:48 PM --%
 s = tf('s');
 P1 = 1/(s+1);
 bode(P1);
 norm(P1, 'inf')
 P2 = 1/(s^2 + 0.1*s + 1);
 bode(P2);
 norm(P2, 'inf')
 ex1008

#ref(2015.10.08-1.jpg,left,noimg,whiteboard #1);
#ref(2015.10.08-2.jpg,left,noimg,whiteboard #2);
#ref(2015.10.08-3.jpg,left,noimg,whiteboard #3);
#ref(2015.10.08-4.jpg,left,noimg,whiteboard #4);
#ref(2015.10.08-5.jpg,left,noimg,whiteboard #5);

-Q: 最後にfを求めてどうするのか分からなかった。
-A: 閉ループ系のH∞ノルムを最小化するfを求め、LQRの最適解と比較する予定でしたが、最後まで説明できずすみません。

-Q: |Tzw|∞ は感度関数になる?
-A: Tzw が感度関数になるか?という意味と思いますが、一般化プラントの設定次第でそうなります(例えば目標値信号を w、偏差を z に選ぶ場合など)。次々回、その場合を扱います。

** &color(green){[lecture #5]}; 2015.10.15 relation between LQR and H infinity control problem (2/2) [#w4c0811d]

+ complete the table in simple example
+ behavior of hinfsyn in &ref(ex1008.m);
+ confirm the cost function J for both controllers by simulation &ref(mod1015.mdl);
+ confirm the closed-loop H infinity norm for both controllers by simulation (common mdl file is available)
-- review: steady-state response (see photo 8 @ lec. #2)
-- how to construct the worst-case disturbance w(t) which maximizes L2 norm of z(t) ?
-- what is the worst-case disturbance in the simple example ?  
+ general case: &ref(hinf.pdf); includes the simple example as a special case
-- LQR &ref(lqr.pdf); is included as a special case where gamma -> infinity, non-zero x(0), and B2 -> B

 %-- 10/15/2015 1:14 PM --%
 ex1008
 K
 dcgain(K)
 gopt
 ex1008
 mod1015
 f
 f = 1
 x0 = 0
 h = 0.1
 zz
 zz(end)
 h = 1e-6
 zz(end)
 f = -1+sqrt(2)
 h
 zz(end)
 x0 = 1
 zz(end)
 f
 h
 h = 10
 zz(end)/ww(end)
 x0
 x0 = 0
 zz(end)/ww(end)
 sqrt(zz(end)/ww(end))
 h
 h = 100
 sqrt(zz(end)/ww(end))

#ref(2015.10.15-1.jpg,left,noimg,whiteboard #1);
#ref(2015.10.15-2.jpg,left,noimg,whiteboard #2);


** &color(green){[lecture #6]}; 2015.10.22 Mixed sensitivity problem 1/3 [#tfbf02f5]

+ review &ref(map_v1.0_intro1.pdf); and outline
+ H infinity control problem (general form)
+ reference tracking problem
+ weighting function for sensitivity function
+ design example &ref(ex1022_1.m); &ref(ex1022_2.m);
+ the small gain theorem
-- proof: Nyquist stability criterion
+ from performance optimization to robust stabilization

 %-- 10/22/2015 2:06 PM --%
 ex1022_1
 eig(P)
 ex1022_2

#ref(2015.10.22-1.jpg,left,noimg,whiteboard #1);
#ref(2015.10.22-2.jpg,left,noimg,whiteboard #2);
#ref(2015.10.22-3.jpg,left,noimg,whiteboard #3);

** &color(green){[lecture #7]}; 2015.10.29 Mixed sensitivity problem 2/3 [#dd1fc284]

+ review &ref(map_v1.0_intro2.pdf); and outline
+ an equivalent problem of robust stabilization for reference tracking problem
+ uncertainty model and normalized uncertainty Delta
+ robust stabilization problem and an equivalent problem 
+ practical example of plant with perturbation &ref(ex1029_1.m);
+ how to determine the model &ref(ex1029_2.m);
+ design example and simulation &ref(ex1029_3.m); &ref(mod1029.mdl);

 %-- 10/29/2015 1:52 PM --%
 ex1029_1
 ex1029_2
 ex1029_3
 mod1029
 c
 c = 0.8

#ref(2015.10.29-1.jpg,left,noimg,whiteboard #1);
#ref(2015.10.29-2.jpg,left,noimg,whiteboard #2);
#ref(2015.10.29-3.jpg,left,noimg,whiteboard #3);

** &color(green){[lecture #8]}; 2015.11.5 Mixed sensitivity problem 3/3 [#oc5e65d6]
+ review : (1)robust stabilization and (2)performance optimization
+ mixed sensitivity problem : a sufficient condition for (1) and (2)
-- proof by definition of H infinity norm
+ construction of the generalized plant
+ design example &ref(ex1105_1.m);
+ gamma iteration by bisection method &ref(ex1105_2.m);
+ a problem of the mixed sensitivity problem: nominal performance and robust performance &ref(ex1105_3.m); 
+ introduction of robust performance problem

 %-- 11/5/2015 1:37 PM --%
 ex1105_1
 ex1105_2
 gam
 ex1105_2
 WT
 ex1105_2
 ex1105_3
 ex1105_2
 ex1105_3

#ref(2015.11.05-1.jpg,left,noimg,whiteboard #1);
#ref(2015.11.05-2.jpg,left,noimg,whiteboard #2);
#ref(2015.11.05-3.jpg,left,noimg,whiteboard #3);

** &color(green){[lecture #9]}; 2015.11.12 robust performance problem 1/3 [#tae1c2b9]
-- [[schedule2015]] mini report and exam
+ review: robust performance problem
+ an equivalent robust stability problem
+ definition of H infinity norm for general case (MIMO)
+ definition of (maximum) singular value
 M = [j, 0; -j, 1]
 M'
 eig(M'*M)
 svd(M)
+ mini report #1 &ref(report1.pdf);
-- write by hand
-- due date and place of submission -> see [[schedule2015]]
-- check if your answer is correct or not before submission by using Matlab
-- You will have a mini exam #1 related to this report
+ SVD: singular value decomposition
-- definition
 [U,S,V] = svd(M)
 M = [j, 0; -j, 1; 2, 3]
-- unitary matrix and 2 norm of vectors
-- a property of SVD: input-output interpretation
-- illustrative example: rotation matrix &ref(ex1112_1.m);
+ H infinity norm of Delta hat

//■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■
&color(black,red){&size(20){!!! the remaining page is under construction (the contents below are from 2014) !!!};};
//


 %-- 10/16/2014 1:00 PM --%
 M = [j, 0; -j, 1]
 M
 svd(M)
 sqrt((3+sqrt(5))/2)
 M'
 M'*M
 ex1016

#ref(2014.10.16-4.jpg,left,noimg,whiteboard #4);
#ref(2014.10.16-5.jpg,left,noimg,whiteboard #5);
#ref(2014.10.16-6.jpg,left,noimg,whiteboard #6);

#ref(ex1023_2.m);
#ref(ex1023_3.m);

 %-- 10/23/2014 12:58 PM --%
 ex1023_1
 A
 S
 V
 V'*V
 V'*V(:,1)
 ex1009_1
 ex1009_2
 ex1023_2
 ex1023_3

#ref(2014.10.23-1.jpg,left,noimg,whiteboard #1);
#ref(2014.10.23-2.jpg,left,noimg,whiteboard #2);
#ref(2014.10.23-3.jpg,left,noimg,whiteboard #3);

-Q1: Is H infinity control theory available for discrete-time system ?
-A1: The answer is yes. You can use the same tool hinfsyn in Matlab to design discrete-time controller. If the question is to ask how to implement digital (discrete-time) controller for given continuous-time plant, there are 3 ways to do this: (i) continuous-time H infinity control based design (continuous-time controller is designed, then it is discretized); (ii) discretized H infinity control design (continuous-time plant is discretized first, then discrete-time controller is designed); (iii) sampled-data H infinity control design (discrete-time controller is directly designed for continuous-time plant)     

** &color(green){[lecture #8]}; 2014.10.30 Robust performance problem (2/3) [#la4839f6]

+ return of mini report #1
+ review of the limitation of mixed sensitivity problem
+ definition of robust performance (R.P.) problem (cf. nominal performance problem on white board #6 in photo #4 of lecture #4) ... S is changed to S~
+ review of robust stability (R.S.) problem on white board #5 in photo #5 of lecture #3 ... robust stability against Delta <=> closed-loop system without Delta has less-than-or-equal-to-one H infinity norm (by small gain theorem) 
+ equivalent R.P. problem with structured uncertainty Delta_hat
+ a conservative problem to R.P. with 2-by-2 unstructured uncertainty Delta_tilde
-- example based on the one given in the last lecture
#ref(ex1030_1.m);
-- a check of the conservativeness
#ref(ex1030_2.m);
+ Delta_tilde is larger set than Delta_hat ... conservativeness
+ mini exam #1 
&ref(exam1.pdf);

 %-- 10/30/2014 1:10 PM --%
 ex1023_2
 ex1023_3
 gam_opt
 ex1030_1
 gam_opt

#ref(2014.10.30-1.jpg,left,noimg,whiteboard #1);
#ref(2014.10.30-2.jpg,left,noimg,whiteboard #2);
#ref(2014.10.30-3.jpg,left,noimg,whiteboard #3);
#ref(2014.10.30-4.jpg,left,noimg,whiteboard #4);

** &color(green){[lecture #9]}; 2014.11.13 Robust performance problem (3/3) [#d50833d3]

- return of mini exam #1 
- review
- inclusion relation of two uncertain set (structured and non-structured)
- scaled H infinity control problem
- effect of scaling matrix
- how to determine structure of scaling matrix
- example
#ref(ex1113_1.m);
#ref(ex1113_2.m);
- %%mini report #2%%

 %-- 11/13/2014 12:58 PM --%
 ex1023_2
 gam_opt
 ex1023_3
 ex1030_1
 gam_opt
 ex1113
 ex1113_1
 gam_opt
 ex1113_2

#ref(2014.11.13-1.jpg,left,noimg,whiteboard #1);
#ref(2014.11.13-2.jpg,left,noimg,whiteboard #2);
#ref(2014.11.13-3.jpg,left,noimg,whiteboard #3);
#ref(2014.11.13-4.jpg,left,noimg,whiteboard #4);

** &color(green){[lecture #10]}; 2014.11.20 Robust performance problem (1/3) (cont.) [#k0c92c66]

- review - effect of scaling
- mini report #2
-- write by hand
-- submit at the beginning of next lecture on 27 Nov.
-- check if your answer is correct or not before submission by using Matlab
-- You will have a mini exam #2 related to this report on 4 Dec.
- how to obtain generalized plant by hand
- %%example: H infinity controller design by hand%%

 %-- 11/20/2014 1:11 PM --%
 ex1023_2
 ex1023_3
 ex1030_1
 ex1030_2
 k
 ex1113_1
 ex1113_2
 k
 Delta_hat

#ref(2014.11.20-1.jpg,left,noimg,whiteboard #1);
#ref(2014.11.20-2.jpg,left,noimg,whiteboard #2);
#ref(2014.11.20-3.jpg,left,noimg,whiteboard #3);
#ref(2014.11.20-4.jpg,left,noimg,whiteboard #4);

** &color(green){[lecture #12]}; 2014.12.4 relation between H infinity control and modern control theory (cont.); %%Speed control of two inertia system with servo motor (1/4)%% [#p666d14d]
- return of mini report #2
- contents for the last lecture
- %%speed control of two inertia system with servo motor%%&br;
%%&ref(setup.pdf);%%
- %%frequency response experiment and physical model of speed control system%%&br;
%%&ref(ex1204_1.m);%%&br;
%%&ref(ex1204_2.dat);%%
- mini exam #2

 %-- 12/4/2014 1:28 PM --%
 ex1127
 mod1127
 x0 = 0
 h = 1
 f = 1
 ww
 zz
 h = 10
 ww
 zz
 h = 50
 zz
 h
 zz


#ref(2014.12.4-1.jpg,left,noimg,whiteboard #1);
#ref(2014.12.4-2.jpg,left,noimg,whiteboard #2);

** &color(green){[lecture #13]}; 2014.12.11 Robust control design for a practical system : Speed control of two inertia system with servo motor (1/3) [#x7c8c11b]

- return of mini exam #2
- introduction of experimental setup
#ref(setup.pdf); 
#ref(photo1.jpg,left,noimg);
- objective of control system
++ to reduce the tracking error of the driving motor against disturbance torque
++ robust stabilization against plant variation due to aging degradation
- frequency response experiment and physical model of speed control system
#ref(ex1211_1.m);
#ref(ex1211_2.dat);
#ref(ex1211_3.dat);
#ref(ex1211_4.dat);
- %%determination of nominal plant%%&br;
%%&ref(ex1211_5.m);%%
- %%determination of weighting function%%&br;
%%&ref(ex1211_6.m);%%

 %-- 12/11/2014 1:24 PM --%
 ex1211_1
 frdata
 frdata(:,1)
 P1_jw
 P1_g
 ex1211_1

#ref(2014.12.11-1.jpg,left,noimg,whiteboard #1);

-Q: What is the inertia moment of the load disk ?
-A: It is about 0.0002 (kg m^2) (60mm in diameter, 16mm in inner diameter, 20mm in thick, made by SS400)

-Q: 周波数応答実験について、定常応答になるのにどのくらい待っているか?音が大きくなるのはゲインが高いから?周波数変化のきざみは?
-A: 待ち時間は3秒です。音の発生源はよくわかりませんし、騒音計などで計測したこともありませんが、大きな音が聞こえるのは共振周波数付近です。周波数変化の刻みは常用対数で0.01です。以下に掲載するプログラムソースの freqresp.h 中で指定しています。

** &color(green){[lecture #14]}; 2014.12.18 Robust control design for a practical system : Speed control of two inertia system with servo motor (2/3) [#yac6fbae]

- design example
//-- modeling based on frequency response experiment 
//- design example 1 : PI control
//-- control experiment
//#ref(cont_PI.dat,,,`cont.dat' file for P control);
//#ref(cont_P_order.dat,,,`cont_order.dat' file for P control);
//#ref(result_P.dat);
//#ref(result_openloop.dat);
//#ref(openloop.mp4);
//#ref(ex1.mp4);
//- design example 2 : H infinity control
-- m-files
#ref(freqresp.m);
#ref(nominal.m);
#ref(weight.m);
#ref(cont.m);
#ref(perf.m);
 >> freqresp
 >> nominal
 >> weight
 >> cont
 >> perf
-- control experiment ... see [[participant list2014]]
- report
+design your controller(s) so that the system performance is improved compared with the design 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 sensitivity function
++time response of control experiment
+Why is the performance of your system improved(or unfortunately deteriorated)?
--&size(30){&color(red){due date: 9th(Fri) Jan 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 &size(25){&color(red){cont.dat, cont_order.dat, and cont.mat};}; to kobayasi@nagaokaut.ac.jp &size(30){&color(red){not later than 26th(Fri) Dec};};

- program sources for frequency response experiment
#ref(freqresp.h)
#ref(freqresp_module.c)
#ref(freqresp_app.c)
-- format of datafile
--- 1st column ... frequency (Hz)
--- 2nd column ... gain from T_M to omega_M
--- 3rd column ... phase from T_M to omega_M
--- 4th column ... gain from T_M to omega_L
--- 5th column ... phase from T_M to omega_L
- 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: omega_M (rad/s)
--- 3rd column: T_M (Nm)
--- 4th column: reference speed (rad/s)
--- 5th column: T_L (Nm)
- configuration of control experiment
-- reference signal is generated as described in hinf_module.c: 
 if((t > 1)&&(t < 4)){
   r = 20.0;
 }else{
   r = 10;
 }
-- disturbance torque is specified as described in hinf_module.c:
  if((t > 2)&&(t < 3)){
   d = -0.1;
 }else{
   d = 0;
 }
- calculation of rotational speed
The rotational speed is approximately calculated by using difference for one sampling period in hinf_module.c and freqresp_module.c like:
 theta_rad = (double)read_theta(0) / (double)Pn212 * 2 * M_PI;
 speed_rad = (theta_rad - theta_rad_before) / msg->sampling_period;
 theta_rad_before = theta_rad
where the sampling period is given as 0.25 ms.

[[participant list2014]]

 %-- 12/18/2014 1:01 PM --%
 freqresp
 nominal
 help fitfrd
 weight
 cont
 help c2d
 perf

#ref(2014.12.18-1.jpg,left,noimg,whiteboard #1);
#ref(2014.12.18-2.jpg,left,noimg,whiteboard #2);


** &color(green){[lecture #15]}; 2014.12.25 Robust control design for a practical system : Speed control of two inertia system with servo motor (3/3) [#f5d0b7b4]

-preparation of your own controller(s)

 %-- 12/25/2014 12:58 PM --%
 load cont.mat
 who
 K_opt
 who
 Kd
 who
 Ghat
 load result.dat
 plot(result(:,1), result(:,2))
 plot(result(:,1), result(:,3))
 who
 bode(K_opt)
 bode(Kd)
 Kd1 = Kd
 K_opt1 = K_opt
 load cont.mat
 bode(K_opt1, 'b', K_opt, 'r')
 bode(Kd1, 'b', Kd, 'r')
 Kd_tmp = c2d(K_opt1, 0.000001);
 bode(Kd1, 'b', Kd, 'r', Kd_tmp, 'm')
 clear all
 load cont.mat
 who
 bode(K_opt)
 K_example = K_opt;
 load cont.mat
 bode(K_example, 'b', K_opt, 'r')

#ref(2014.12.25-1.jpg,left,noimg,whiteboard #1);
#ref(2014.12.25-2.jpg,left,noimg,whiteboard #2);

//**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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