基于bp神经网络pid控制程序 基于bp神经网络pid控制程序

				基于bp神经网络pid控制程序
				
				
				%BP based PID Control
				clear all;
				close all;
				
				xite=0.25;
				alfa=0.05;
				
				S=2; %Signal type
				
				IN=4;H=5;Out=3;  %NN Structure
				if S==1  %Step Signal
				   wi=[-0.6394   -0.2696   -0.3756   -0.7023;
				       -0.8603   -0.2013   -0.5024   -0.2596;
				       -1.0749    0.5543   -1.6820   -0.5437;
				       -0.3625   -0.0724   -0.6463   -0.2859;
				       0.1425    0.0279   -0.5406   -0.7660];
				   %wi=0.50*rands(H,IN);
				   wi_1=wi;wi_2=wi;wi_3=wi;
				   wo=[0.7576 0.2616 0.5820 -0.1416 -0.1325;
				       -0.1146 0.2949 0.8352  0.2205  0.4508;
				       0.7201 0.4566 0.7672  0.4962  0.3632];
				   %wo=0.50*rands(Out,H);
				   wo_1=wo;wo_2=wo;wo_3=wo;
				end
				
				if S==2  %Sine Signal
				   wi=[-0.2846    0.2193   -0.5097   -1.0668;
				       -0.7484   -0.1210   -0.4708    0.0988;
				       -0.7176    0.8297   -1.6000    0.2049;
				       -0.0858    0.1925   -0.6346    0.0347;
				       0.4358    0.2369   -0.4564   -0.1324];
				   %wi=0.50*rands(H,IN);
				   wi_1=wi;wi_2=wi;wi_3=wi;
				   wo=[1.0438    0.5478    0.8682    0.1446    0.1537;
				       0.1716    0.5811    1.1214    0.5067    0.7370;
				       1.0063    0.7428    1.0534    0.7824    0.6494];
				   %wo=0.50*rands(Out,H);
				   wo_1=wo;wo_2=wo;wo_3=wo;
				end
				
				x=[0,0,0];
				u_1=0;u_2=0;u_3=0;u_4=0;u_5=0;
				y_1=0;y_2=0;y_3=0;
				
				Oh=zeros(H,1);    %Output from NN middle layer
				I=Oh;             %Input to NN middle layer
				error_2=0;
				error_1=0;
				
				ts=0.001;
				for k=1:1:6000
				   time(k)=k*ts;
				   
				   if S==1
				       rin(k)=1.0;
				   elseif S==2
				       rin(k)=sin(1*2*pi*k*ts);
				   end
				   
				   %Unlinear model
				   a(k)=1.2*(1-0.8*exp(-0.1*k));
				   yout(k)=a(k)*y_1/(1+y_1^2)+u_1;
				   
				   error(k)=rin(k)-yout(k);
				   
				   xi=[rin(k),yout(k),error(k),1];
				   
				   x(1)=error(k)-error_1;
				   x(2)=error(k);
				   x(3)=error(k)-2*error_1+error_2;
				   
				   epid=[x(1);x(2);x(3)];
				   I=xi*wi';
				   for j=1:1:H
				       Oh(j)=(exp(I(j))-exp(-I(j)))/(exp(I(j))+exp(-I(j))); %Middle Layer
				   end
				   K=wo*Oh;             %Output Layer
				   for l=1:1:Out
				       K(l)=exp(K(l))/(exp(K(l))+exp(-K(l)));        %Getting kp,ki,kd
				   end
				   kp(k)=K(1);ki(k)=K(2);kd(k)=K(3);
				   Kpid=[kp(k),ki(k),kd(k)];
				   
				   du(k)=Kpid*epid;
				   u(k)=u_1+du(k);
				   if u(k)>=10       % Restricting the output of controller
				       u(k)=10;
				   end
				   if u(k)				       u(k)=-10;
				   end
				   
				   dyu(k)=sign((yout(k)-y_1)/(u(k)-u_1+0.0000001));
				   
				   %Output layer
				   for j=1:1:Out
				       dK(j)=2/(exp(K(j))+exp(-K(j)))^2;
				   end
				   for l=1:1:Out
				       delta3(l)=error(k)*dyu(k)*epid(l)*dK(l);
				   end
				   
				   for l=1:1:Out
				       for i=1:1:H
				           d_wo=xite*delta3(l)*Oh(i)+alfa*(wo_1-wo_2);
				       end
				   end
				   wo=wo_1+d_wo+alfa*(wo_1-wo_2);
				   %Hidden layer
				   for i=1:1:H
				       dO(i)=4/(exp(I(i))+exp(-I(i)))^2;
				   end
				   segma=delta3*wo;
				   for i=1:1:H
				       delta2(i)=dO(i)*segma(i);
				   end
				   
				   d_wi=xite*delta2'*xi;
				   wi=wi_1+d_wi+alfa*(wi_1-wi_2);
				   
				   %Parameters Update
				   u_5=u_4;u_4=u_3;u_3=u_2;u_2=u_1;u_1=u(k);   
				   y_2=y_1;y_1=yout(k);
				   
				   wo_3=wo_2;
				   wo_2=wo_1;
				   wo_1=wo;
				   
				   wi_3=wi_2;
				   wi_2=wi_1;
				   wi_1=wi;
				   
				   error_2=error_1;
				   error_1=error(k);
				end
				figure(1);
				plot(time,rin,'r',time,yout,'b');
				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');
				figure(4);
				subplot(311);
				plot(time,kp,'r');
				xlabel('time(s)');ylabel('kp');
				subplot(312);
				plot(time,ki,'g');
				xlabel('time(s)');ylabel('ki');
				subplot(313);
				plot(time,kd,'b');
				xlabel('time(s)');ylabel('kd')