Simulink仿真_遗传算法PID控制

%Generic Algorithm for function f(x1,x2) optimum clear all; close all; Size=30; CodeL=3; 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(:,1)=MinX(1)+(MaxX(1)-MinX(1))*rand(Size,1); E(:,2)=MinX(2)+(MaxX(2)-MinX(2))*rand(Size,1); E(:,3)=MinX(3)+(MaxX(3)-MinX(3))*rand(Size,1); G=100;%迭代次数 BsJ=0; %*************** Start Running *************** for kg=1:1:G time(kg)=kg; %****** Step 1 : Evaluate BestJ ****** for i=1:1:Size x=E(i,:); [x,BsJ]=GA_PID_Simulink_fitness(x,BsJ); BsJi(i)=BsJ; end [OderJi,IndexJi]=sort(BsJi); BestJ(kg)=OderJi(1); BJ=BestJ(kg); Ji=BsJi+1e-10; %Avoiding deviding zero fi=1./Ji; [Oderfi,Indexfi]=sort(fi); %Arranging fi small to bigger Bestfi=Oderfi(Size); %Let Bestfi=max(fi) BestS=E(Indexfi(Size),:); %Let BestS=E(m), m is the Indexfi belong to max(fi) bfi(kg)=Bestfi; kg x BJ %****** 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 r=Size-sum(fi_S); Rest=fi_Size-fi_S; [RestValue,Index]=sort(Rest); for i=Size:-1:Size-r+1 fi_S(Index(i))=fi_S(Index(i))+1; % Adding rest to equal Size end k=1; for i=Size:-1:1 % Select the Sizeth and Reproduce firstly for j=1:1:fi_S(i) TempE(k,:)=E(Indexfi(i),:); % Select and Reproduce k=k+1; % k is used to reproduce end end %************ Step 3 : Crossover Operation ************ Pc=0.90; for i=1:2:(Size-1) temp=rand; if Pc>temp %Crossover Condition alfa=rand; TempE(i,:)=alfa*E(i+1,:)+(1-alfa)*E(i,:); TempE(i+1,:)=alfa*E(i,:)+(1-alfa)*E(i+1,:); end end TempE(Size,:)=BestS; E=TempE; %************ Step 4: Mutation Operation ************** Pm=0.10-[1:1:Size]*(0.01)/Size; %Bigger fi,smaller Pm Pm_rand=rand(Size,CodeL); Mean=(MaxX + MinX)/2; Dif=(MaxX-MinX); for i=1:1:Size for j=1:1:CodeL if Pm(i)>Pm_rand(i,j) %Mutation Condition TempE(i,j)=Mean(j)+Dif(j)*(rand-0.5); end end end %Guarantee TempE(Size,:) belong to the best individual TempE(Size,:)=BestS; E=TempE; end BestS Bestfi fi x Best_J=BestJ(G) figure(1); plot(time,BestJ); xlabel('Times');ylabel('Best J'); save pfile x;