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%chap5_3.m 
%GA(Generic Algorithm) Program is to optimize Parameters of PID 
clear all; 
close all; 
global rin yout timef 
 
G=100; 
Size=30; 
CodeL=10; 
 
MinX(1)=zeros(1); 
MaxX(1)=20*ones(1); 
MinX(2)=zeros(1); 
MaxX(2)=1.0*ones(1); 
MinX(3)=zeros(1); 
MaxX(3)=1.0*ones(1); 
 
E=round(rand(Size,3*CodeL));    %Initial Code! 
 
BsJ=0; 
 
for kg=1:1:G 
time(kg)=kg; 
     
for s=1:1:Size 
m=E(s,:); 
y1=0;y2=0;y3=0; 
 
m1=m(1:1:CodeL); 
for i=1:1:CodeL 
   y1=y1+m1(i)*2^(i-1); 
end 
Kpid(s,1)=(MaxX(1)-MinX(1))*y1/1023+MinX(1); 
 
m2=m(CodeL+1:1:2*CodeL); 
for i=1:1:CodeL 
   y2=y2+m2(i)*2^(i-1); 
end 
Kpid(s,2)=(MaxX(2)-MinX(2))*y2/1023+MinX(2); 
 
m3=m(CodeL+1:1:2*CodeL); 
for i=1:1:CodeL 
   y3=y3+m3(i)*2^(i-1); 
end 
Kpid(s,3)=(MaxX(3)-MinX(3))*y3/1023+MinX(3); 
 
%****** Step 1 : Evaluate BestJ ****** 
Kpidi=Kpid(s,:); 
     
[Kpidi,BsJ]=chap5_2f(Kpidi,BsJ); 
 
 BsJi(s)=BsJ;    
 end 
  
[OderJi,IndexJi]=sort(BsJi); 
BestJ(kg)=OderJi(1); 
BJ=BestJ(kg); 
Ji=BsJi+1e-10; 
 
   fi=1./Ji; 
%  Cm=max(Ji); 
%  fi=Cm-Ji;        %Avoiding deviding zero 
    
   [Oderfi,Indexfi]=sort(fi);          %Arranging fi small to bigger 
%   Bestfi=Oderfi(Size);               %Let Bestfi=max(fi) 
%   BestS=Kpid(Indexfi(Size),:);       %Let BestS=E(m), m is the Indexfi belong to max(fi) 
 
Bestfi=Oderfi(Size);           % Let Bestfi=max(fi) 
BestS=E(Indexfi(Size),:);      % Let BestS=E(m), m is the Indexfi belong to max(fi) 
 
kg    
BJ 
BestS; 
 
%****** Step 2 : Select and Reproduct Operation****** 
   fi_sum=sum(fi); 
   fi_Size=(Oderfi/fi_sum)*Size; 
    
   fi_S=floor(fi_Size);        %Selecting Bigger fi value 
    
   kk=1; 
   for i=1:1:Size 
      for j=1:1:fi_S(i)        %Select and Reproduce  
       TempE(kk,:)=E(Indexfi(i),:);   
         kk=kk+1;              %kk is used to reproduce 
      end 
   end 
    
%************ Step 3 : Crossover Operation ************ 
pc=0.60; 
n=ceil(20*rand); 
for i=1:2:(Size-1) 
    temp=rand; 
    if pc>temp                 %Crossover Condition 
    for j=n:1:20 
        TempE(i,j)=E(i+1,j); 
        TempE(i+1,j)=E(i,j); 
    end 
    end 
end 
TempE(Size,:)=BestS; 
E=TempE; 
    
%************ Step 4: Mutation Operation ************** 
%pm=0.001; 
pm=0.001-[1:1:Size]*(0.001)/Size; %Bigger fi, smaller pm 
%pm=0.0;    %No mutation 
%pm=0.1;    %Big mutation 
 
   for i=1:1:Size 
      for j=1:1:2*CodeL 
         temp=rand; 
         if pm>temp               %Mutation Condition 
            if TempE(i,j)==0 
               TempE(i,j)=1; 
            else 
               TempE(i,j)=0; 
            end 
        end 
      end 
   end 
%Guarantee TempE(Size,:) belong to the best individual 
TempE(Size,:)=BestS; 
E=TempE; 
%******************************************************* 
 end 
  
 Bestfi 
 BestS 
 Kpidi 
 Best_J=BestJ(G) 
 figure(1); 
 plot(time,BestJ); 
 xlabel('Times');ylabel('Best J'); 
 figure(2); 
 plot(timef,rin,'r',timef,yout,'b'); 
 xlabel('Time(s)');ylabel('rin,yout');