基于神经网络输出反馈的动态矩阵控制研究.docx

clear all;close all;xite=0.50;alfa=0.05;w2=rand(6,1);w2_1=w2;w2_2=w2;w1=rand(2,6);w1_1=w1;w1_2=w1;dw1=0*w1;x=[0,0];u_1=0;y_1=0;I=[0,0,0,0,0,0];Iout=[0,0,0,0,0,0];FI=[0,0,0,0,0,0];ts=0.001;for k=1:1:1000time(k)=k*ts;u(k)=0.50*sin(3*2*pi*k*ts);a(k)=1.2*(1-0.8*exp(-0.1*k));y(k)=a(k)*y_1/(1+y_1^2)+u_1;for j=1:1:6 I(j)=x*w1(:,j); Iout(j)=1/(1+exp(-I(j)));endyn(k)=w2*Iout;e(k)=y(k)-yn(k);w2=w2_1+(xite*e(k))*Iout+alfa*(w2_1-w2_2);for j=1:1:6 FI(j)=exp(-I(j))/(1+exp(-I(j)))^2;endfor i=1:1:2 for j=1:1:6 dw1(i,j)=e(k)*xite*FI(j)*w2(j)*x(i); endendw1=w1_1+dw1+alfa*(w1_1-w1_2);x(1)=u(k);x(2)=y(k);w1_2=w1_1;w1_1=w1;w2_2=w2_1;w2_1=w2;u_1=u(k);y_1=y(k);endfigure(1);plot(time,y,r,time,yn,b);xlabel(times);ylabel(y and yn);grid onts=0.1;for k=1:1:200time(k)=k*ts;u(k)=1;a(k)=1.2*(1-0.8*exp(-0.1*k));y(k)=a(k)*y_1/(1+y_1^2)+u_1;for j=1:1:6 I(j)=x*w1(:,j); Iout(j)=1/(1+exp(-I(j)));endyn(k)=w2*Iout;e(k)=y(k)-yn(k);w2=w2_1+(xite*e(k))*Iout+alfa*(w2_1-w2_2);for j=1:1:6 FI(j)=exp(-I(j))/(1+exp(-I(j)))^2;endfor i=1:1:2 for j=1:1:6 dw1(i,j)=e(k)*xite*FI(j)*w2(j)*x(i); endendw1=w1_1+dw1+alfa*(w1_1-w1_2);x(1)=u(k);x(2)=y(k);w1_2=w1_1;w1_1=w1;w2_2=w2_1;w2_1=w2;u_1=u(k);y_1=y(k);y0(k)=yn(k);endTs=5;N=200;P=25;m=20;Sv=10;yg_1=0;A=zeros(P,m);a=zeros(N,1);for i=1:N a(i)=y0(i);endfor i=1:P for j=1:m if i-j+10 A(i,j)=a(i-j+1); end endendK=inv(A*A+eye(m))*A;y=zeros(N,1);u=zeros(N,1);e=zeros(N,1);A0=zeros(P,N-1);for i=1:P for j=N-2:-1:1 if N-j+1+i-1=N A0(i,j)=a(N-j+1+i-1)-a(N-j+i-1); else A0(i,j)=0; end end A0(i,N-1)=a(i+1);endfor k=2:N Uk_1=zeros(N-1,1); for i=1:N-1 if k-N+i=0 Uk_1(i)=0; else Uk_1(i)=u(k-N+i); end end Y0=A0*Uk_1;a(k)=1.2*(1-0.8*exp(-0.1*k));yg(k)=a(k)*y_1/(1+y_1^2)+u_1;u_1=u(k); yg_1=yg(k); e(k)=y(k)-yg(k); Ysk=zeros(P,1); for i=1:P Ysk(i)=Sv; end Ek=zeros(P,1); for i=1:P Ek(i)=0