Kakoli Majumder

codes are as follows:

setlmis([]);

%% LMI variables

X=lmivar(1,[3 1]);

A=lmivar(3,[-1 1 0;0 0 1;0 0 0]);

B_tilde=lmivar(3,[1 0 0;0 0 1;0 1 0]);

I=lmivar(3,[1 0 0;0 1 0;0 0 1]);

% LMI commands

%First LMI

lmiterm([1 1 1 -B_tilde],.5*1,(A*X+X*A'+0.1667*I)*B_tilde,'s'); % LMI #1: B_tilde'* (A*X+X*A'+0.1667*I)*B_tilde (NON SYMMETRIC?)

lmiterm([1 2 1 B_tilde],0.3896,1); % LMI #1: 0.3896*B_tilde

lmiterm([1 2 2 I],1,-1); % LMI #1: -I

lmiterm([1 3 1 A],1,X*B_tilde); % LMI #1: A*X*B_tilde

lmiterm([1 3 2 I],0.3896,1); % LMI #1: 0.3896*I

lmiterm([1 3 3 I],.5*0.7611,-1,'s'); % LMI #1: -0.7611*I (NON SYMMETRIC?)

lmiterm([1 4 1 X],0.2,B_tilde); % LMI #1: 0.2*X*B_tilde

lmiterm([1 4 4 I],.5*0.1667,-1,'s'); % LMI #1: -0.1667*I (NON SYMMETRIC?)

lmiterm([1 5 1 X],0.2,B_tilde); % LMI #1: 0.2*X*B_tilde

lmiterm([1 5 5 I],.5*0.2389,-1,'s'); % LMI #1: -0.2389*I (NON SYMMETRIC?)

%Second LMI

lmiterm([-2 1 1 X],1,1); % LMI #2: X

lmiterm([-2 2 1 I],1,1); % LMI #2: I

lmiterm([-2 2 2 I],.5*19.7926,1,'s'); % LMI #2: 19.7926*I (NON SYMMETRIC?)

lmiterm([-2 3 3 I],.5*24.0829,1,'s'); % LMI #2: 24.0829*I (NON SYMMETRIC?)

lmiterm([-2 3 3 X],1,-1); % LMI #2: -X

lmiterm([-2 4 4 0],2*0.3896*0.25-0.1*(19.7926+24.0829)); % LMI #2: 2*0.3896*0.25-0.1*(19.7926+24.0829)

lmisys=getlmis;

[tmin,xfeas]=feasp(lmisys);

X=dec2mat(lmisys,xfeas,X)

P=inv(X)

Solution : 

Solver for LMI feasibility problems L(x) < R(x)

This solver minimizes t subject to L(x) < R(x) + t*I

The best value of t should be negative for feasibility

Iteration : Best value of t so far

1 4.940191

*** new lower bound: 1.990739

Result: best value of t: 4.940191

f-radius saturation: 0.000% of R = 1.00e+009

These LMI constraints were found infeasible

X=[-0.0044 0 0;0 -0.0308 0;0 0 -0.0308]

P =[-227.2183 0 0;0 -32.4559 0;0 0 -32.4559]

written codes are somehow wrong, so that founded results are infeasible..but I am not able to clarify where I am wrong....

Thanking You