single neural adaptive pid controller.m

单神经元自适应pid算法matlab原程序

%Single Neural Adaptive PID Controller
clear all;
close all;

x=[0,0,0]';

xiteP=0.40;
xiteI=0.35;
xiteD=0.40;

%Initilizing kp,ki and kd
wkp_1=0.10;
wki_1=0.10;
wkd_1=0.10;
%wkp_1=rand;
%wki_1=rand;
%wkd_1=rand;

error_1=0;
error_2=0; 
y_1=0;y_2=0;y_3=0;
u_1=0;u_2=0;u_3=0;

ts=0.001;
for k=1:1:1000
    time(k)=k*ts;
    rin(k)=0.5*sign(sin(2*2*pi*k*ts));
    yout(k)=0.368*y_1+0.26*y_2+0.1*u_1+0.632*u_2;
    error(k)=rin(k)-yout(k);
   
%Adjusting Weight Value by hebb learning algorithm
    M=4;
    if M==1              %No Supervised Heb learning algorithm 
        wkp(k)=wkp_1+xiteP*u_1*x(1);  %P
        wki(k)=wki_1+xiteI*u_1*x(2);  %I
        wkd(k)=wkd_1+xiteD*u_1*x(3);  %D
        K=0.06;   
    elseif M==2          %Supervised Delta learning algorithm 
        wkp(k)=wkp_1+xiteP*error(k)*u_1;  %P
        wki(k)=wki_1+xiteI*error(k)*u_1;  %I
        wkd(k)=wkd_1+xiteD*error(k)*u_1;  %D
        K=0.12;   
   elseif M==3          %Supervised Heb learning algorithm 
        wkp(k)=wkp_1+xiteP*error(k)*u_1*x(1);  %P
        wki(k)=wki_1+xiteI*error(k)*u_1*x(2);  %I
        wkd(k)=wkd_1+xiteD*error(k)*u_1*x(3);  %D
        K=0.12;   
   elseif M==4          %Improved Heb learning algorithm 
        wkp(k)=wkp_1+xiteP*error(k)*u_1*(2*error(k)-error_1);
        wki(k)=wki_1+xiteI*error(k)*u_1*(2*error(k)-error_1);
        wkd(k)=wkd_1+xiteD*error(k)*u_1*(2*error(k)-error_1); 
        K=0.22;   
    end
   
    x(1)=error(k)-error_1;             %P
    x(2)=error(k);                     %I
    x(3)=error(k)-2*error_1+error_2;   %D

    wadd(k)=abs(wkp(k))+abs(wki(k))+abs(wkd(k));
    w11(k)=wkp(k)/wadd(k);
    w22(k)=wki(k)/wadd(k);
    w33(k)=wkd(k)/wadd(k);
    w=[w11(k),w22(k),w33(k)];

	u(k)=u_1+K*w*x;     %Control law

    if u(k)>10
        u(k)=10;
    end   
    if u(k)<-10
        u(k)=-10;
    end   
  
    error_2=error_1;
    error_1=error(k);
   
    u_3=u_2;u_2=u_1;u_1=u(k);
    y_3=y_2;y_2=y_1;y_1=yout(k);
       
    wkp_1=wkp(k);
    wkd_1=wkd(k);
    wki_1=wki(k);
end
figure(1);
plot(time,rin,'b',time,yout,'r');
xlabel('time(s)');ylabel('rin,yout');
figure(2);
plot(time,error,'r');
xlabel('time(s)');ylabel('error');
figure(3);
plot(time,u,'r');
xlabel('time(s)');ylabel('u');