chap5_2.m

里面汇集了很多经典的pid控制程序

%Generic Algorithm for function f(x1,x2) optimum
clear all;
close all;

Size=100;
CodeL=2;

MinX(1)=-2.048;
MaxX(1)=2.048;
MinX(2)=-2.048;
MaxX(2)=2.048;

E(:,1)=MinX(1)+(MaxX(1)-MinX(1))*rand(Size,1);
E(:,2)=MinX(2)+(MaxX(2)-MinX(2))*rand(Size,1);

G=500;
BsJ=0;

tic
%*************** Start Running ***************
for kg=1:1:G
    time(kg)=kg;

    %****** Step 1 : Evaluate BestJ ******
    for i=1:1:Size
        xi=E(i,:);
        x1=xi(1);
        x2=xi(2);

        F(i)=100*(x1^2-x2)^2+(1-x1)^2;

        Ji=1./F;
        BsJi(i)=min(Ji);

    end

    [OderJi,IndexJi]=sort(BsJi);
    BestJ(kg)=OderJi(1);
    BJ=BestJ(kg);
    Ji=BsJi+1e-10;    %Avoiding deviding zero

    fi=F;

    [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;
    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
    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
toc

BestS
Bestfi

figure(1);
subplot(211);
plot(time,BestJ,'k');
xlabel('Times');ylabel('Best J');

subplot(212);
plot(time,bfi,'k');
xlabel('times');ylabel('Best F');