ilc.rar_ILC_ILC control_iterative learning_matlab ILC

clear all; close all; m=20; n=100; gama=0.9; x1(1:m,1:n)=0; x2(1:m,1:n)=0; u(1:m,1:n)=0; y(1:m,1:n)=0; e(1:m,1:n)=0; err(1:m,1:n)=0; % b=beronulli(1,1000,1); % w=randn(m,n)/5; for n=1:100 y_d(n) = sin(8*(n-1)/50); %y_d(n) = 5*sin(n*pi/100)+0.3*cos(n*pi/100); % if n<=300 % y_d(n) =5*(-1).^round(n/100); % else if n<=700 % y_d(n) = 5*sin(n*pi/100)+0.3*cos(n*pi/100); % else % y_d(n) =5*(-1).^round(n/100); % end % end %y_d(n)=12*n.^2*(n-1); %y_d(n) = sin(2*pi*n/50); end for k=1:m for t=2:n-1 x1(k,t)=(-0.8*x1(k,t-1))-0.22*x2(k,t-1)+0.5*u(k,t-1); x2(k,t)=x1(k,t-1)+u(k,t-1); y(k,t-1)=(x1(k,t-1)+0.5*x2(k,t-1)); e(k,t-1)=y_d(t-1)-y(k,t-1); err(k,t-1)=abs(e(k,t-1)).^2; end for t=2:n-1 u(k+1,t-1)=u(k,t-1)+gama*e(k,t)+0.3*e(k,t-1); end errn(k)=max(err(k,:)); end plot(y_d(1:90),'-r');hold on plot(y(1,1:90));hold on; plot(y(2,1:90));hold on; plot(y(3,1:90));hold on; plot(y(5,1:90));hold on; % plot(y(8,1:90));hold on; %plot(y(10,1:90));hold on; %plot(y(15,1:90));hold on; figure plot(err(5,1:90)); %plot(err(12,1:20));hold on %plot(err(15,1:20));hold on k=1:20; figure;plot(k,errn(k))