I'm using LMILab solver for Lyapunov stability LMI but getting an objective value NAN. Which solver is the best for this kind of problem?
A=data.A;
B=data.B;
LMI1=[];
LMI2=[];
LMI3=[];
LMI4=[];
X=sdpvar(ni);
for i=1:nr
Y{i}=sdpvar(nu,ni);
Q{i}=sdpvar(ni);
end
for r=1:nr
Ar=A(:,:,r);
Br=B(:,:,r);
LMI1= LMI1 + setLMI1(Ar,Br,Q{r},Y{r}, X,nr);
end
for i=1:nr
for j=i:nr
Ai=A(:,:,i);
Aj=A(:,:,j);
Bi=B(:,:,i);
Bj=B(:,:,j);
LMI2= LMI2 + setLMI2(Ai,Aj,Bi,Bj, Q{i},Q{j},Y{i}, Y{j}, X);
end
end
for r=1:nr
LMI3 = LMI3 + set(Q{r}>0);
% LMI4 = LMI4 +set(Q{r}<500*eye(ni));
end
LMI5=set(X>=0);
ineqs = LMI1 + LMI2 + LMI3 + LMI4 + LMI5;
gamma2=0;
for r=1:nr
gamma2=gamma2+norm(double(Y{r})*inv(double(Q{r})));
end
opts=sdpsettings;
opts.solver='lmilab';
opts = sdpsettings(opts,'verbos',0);
% warning('off','YALMIP:strict')
yalmipdiagnostics=solvesdp(ineqs,gamma2,opts);