singleneuraladaptivepidcontroller.m

单神经元自适应pid,减少了模型误差对远程控制系统的影响,试验表明系统具有良好的鲁棒性和控制品质

%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)=1.0;
    %rin(k)=sin(1*2*pi*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=0.12;   
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)];%Kp,Ki,Kd,
   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');
legend('rin','yout');
figure(2);
plot(time,error,'r');
xlabel('time(s)');ylabel('error');
figure(3);
plot(time,u,'r');
xlabel('time(s)');ylabel('u');