How can I tune the PID controller using Genetic Algorithms?

% intialising the population of Genetic Algorithms populationSize=80; variableBounds=[-100 100;-100 100;-100 100]; evalFN='Initial_PID_objfun_mse'; evalOps=[]; options=[1e-6 1]; initPop=initialize(populationSize,variableBounds,evalFN,evalOps,options); % Intilalising the parameters for the Genetic Algorithms bounds=[-100 100;-100 100;-100 100]; evalFN='Initial_PID_objfun_mse'; evalOps=[]; startPop=initPop; options=[1e-6 1 0]; termFN='maxGenTerm'; termOps=100; selectFN='normGeomSelect'; selectOps=0.08; xOverOps=4; mutFNs='multiNonUnifMutation'; mut1ops=[8 100 2]; %Performing the Genetic Algorithms [x,endPop,bPop,traceInfo]=ga(bounds,evalFN,evalOps,startPop,options,termFN,termmOps,selectFN,selectOps,xOverOps,mutFNs,mutOps); function [x_pp,fx_val]=PID_objfun_MSE(x_pop,options) %slitting the chromosome up into its 3 separate strings Kp=x_pop(2); Ki=x_pop(3); Kd=x_pop(1); %Creating the PID controller from current values pid_den=[1 0]; pid_num=[Kd Kp Ki]; pid_sys=tf(pid_num,pid_den); time=0:0.1:30; [y t]=step(sys_controlled,time); for i=1:301 error(i)=1-y(i); end %to make sure controlled system is stable poles=pole(sys_controlled); if poles(1)>0 error=100e300; elseif poles(2)>0 error=100e300; elseif poles(3)>0 error=100e300; elseif poles(4)>0 error=100e300; elseif poles(5)>0 error=100e300; end