fminimax

Hello everyone,

I have to study robustness of my system, so my variables are uncertain and I have to add another variable to my objective function and it becomes:

original objective-function: myfun = @(x) sum (x(1:n)./polyval(p3,x(1:n)));

robust optimization : min max myfun = @(x) sum ([x(1:n) + r(1:n)]./polyval(p3,[x(1:n) + r(1:n)])); min for "x" and max for "r" .

"r" is the perturbation so it is very small,

my problem is non-convex and with non-linear constraints, and I solve the original problem with fmincon and it provides a good optimum.

For the robust optimization, I think that I can solve it by the fminimax, but I don't know how formulate it ??

Thanks,