LMI Minicx Problem (Robust Control)
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This Theorem is from one paper published in IEEE Trans Automatic Control, the details of theorem are as follows:
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Then, I using the following configurations to test this theorem
alpha = -0.07, and beta is -0.28, delta is equal to 0.5.
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If I want to find the miniman vlaue of gamma, i have the following LMI equation
Minimise gamma subject to (10)
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Finally, I develop my own code, please see the following. However, it cannot work well, is there anyone can provide me some advice? Thanks a lot.
%% system definitation
delta = 0.5;
A = [delta 0.8 -0.4; -0.5 0.4 0.5; 1.2 1.1 0.8];
B = [0 1; 2 -1; 0 1.3];
E = [0.1; 0.4; 0.1];
C1 = [-1 0 2];
D = [0 0];
F = 0.3;
C2 = [-1 1.2 1; 0 -3 1];
H = [0.1; 0.4];
alpha = -0.07;
beta = -0.28;
A_bar = [A E; C1 F];
B_bar = [B; D];
% K_bar = K;
C_bar = [C2 H];
%% define the LMI system
setlmis([]);
%% Defining Variables:
gamma = lmivar(1, [1 0]); % gamma(1,1)
[P, n, sP] = lmivar(2, [2 2]); % P(2,2)
[G, n, sG] = lmivar(2, [4 4]); % G(4,4)
[V, n, sV] = lmivar(2, [2 2]); % V(2,2)
[U, n, sU] = lmivar(2, [2 2]); % U(2,2)
[J, n, sJ] = lmivar(2, [4 4]); % J(4,4)
[Xi_11, n, sXi_11] = lmivar(3, [sP, zeros(2, 2); zeros(2, 2), -gamma*gamma*eye(2, 2)]);
[Xi_22_bar, n, sXi_22_bar] = lmivar(3, [sP, zeros(2, 2); zeros(2, 2), eye(2, 2)]);
[Xi_22, n, sXi_22] = lmivar(3, [-alpha*(sG)-alpha*((sG)')+alpha*alpha*(sXi_22_bar)]);
%% Defining LMIs term contents:
% DEFINITION 1-st row
lmiterm([1 1 1 Xi_11], 1, 1); % #1 LMI, the (1, 1) block
% DEFINITION 2-nd row
lmiterm([1 2 1 G], 1, A_bar); % #1 LMI, the (2, 1) block
lmiterm([1 2 1 V], B_bar, C_bar); % #1 LMI, the (2, 1) block
lmiterm([1 2 2 Xi_22], 1, 1); % #1 LMI, the (2, 2) block
lmiterm([1 2 2 J], 1, 1); % #1 LMI, the (2, 2) block
% DEFINITION 3-rd row
lmiterm([1 3 1 V], ((B_bar')*B_bar), C_bar); % #1 LMI, the (3, 1) block
lmiterm([1 3 2 0], 0); % #1 LMI, the (3, 2) block
lmiterm([1 3 3 U], beta*((B_bar')*B_bar), -1, 's'); % #1 LMI, the (3, 3) block
% DEFINITION 4-th row
lmiterm([1 4 1 0], 0); % #1 LMI, the (4, 1) block
lmiterm([1 4 2 0], 0); % #1 LMI, the (4, 2) block
lmiterm([1 4 3 G], 1, B_bar); % #1 LMI, the (4, 3) block
lmiterm([1 4 3 U], B_bar, -1); % #1 LMI, the (4, 3) block
lmiterm([1 4 4 J], (1/(beta*beta)), -1); % #1 LMI, the (4, 4) block
lmisys = getlmis;
%% check the feasibility
% [tmin, xfeas] = feasp(lmisys);
% V = dec2mat(lmisys, xfeas, V);
% U = dec2mat(lmisys, xfeas, U);
%% Defining vector "c" for C'x in mincx
Num = decnbr(lmisys);
c = zeros(Num,1);
c(Num)=1;
%% Solving LMIs:
[copt,xopt] = mincx(lmisys,c);
%% Finding Feedback gain and u:
% display(gopt)
% K = inv(U)*V
采纳的回答
yan zong
2019-10-30
0 个投票
6 个评论
Muhammad Atif
2020-4-26
yes sir I have a similar algorithem. Can you help me to solve??
Habor lee
2021-3-15
Hi Yan,
Could you please send a copy to me? 979685101@qq.com? Thanks a lot!
GOVIND PRASAD PANDIYA
2022-2-14
can you help for roesser model LMI
sharmin islam
2022-8-13
Hello, I have a similar Question. Can you please help me solve it also?
超
2023-7-20
Hi zong, please send a copy to me, thank you very much, gechao365@126.com.
REVATHI
2024-10-22
Hi Yan ,I have a simillar problem ,Can you send the code ,its help to solve my problem please
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