智能控制(神经网络)-作业 (2).doc

智能控制作业学生姓名： 学 号： 专业班级： 7-2 采用BP网路、RBF网路、DRNN网路逼近线性对象，分别进行matlab仿真。 （1） 采用BP网络仿真网络结构为2-6-1。采样时间1ms，输入信号，权值的初值随机取值，。仿真m文件程序为：%BP simulationclear all;clear all;xite=0.5;alfa=0.5;w1=rands(2,6); % value of w1,initially by randomw1_1=w1;w1_2=w1;w2=rands(6,1); % value of w2,initially by randomw2_1=w2;w2_2=w2_1;dw1=0*w1;x=0,0;u_1=0;y_1=0;I=0,0,0,0,0,0; % input of yinhanceng cellIout=0,0,0,0,0,0; % output of yinhanceng cellFI=0,0,0,0,0,0;ts=0.001;for k=1:1:1000 time(k)=k*ts; u(k)=0.5*sin(3*2*pi*k*ts); y(k)=(u_1-0.9*y_1)/(1+y_12); for j=1:1:6 I(j)=x*w1(:,j); Iout(j)=1/(1+exp(-I(j); end yn(k)=w2*Iout; %output of network e(k)=y(k)-yn(k); % error calculation w2=w2_1+(xite*e(k)*Iout+alfa*(w2_1-w2_2); % rectify of w2 for j=1:1:6 FI(j)=exp(-I(j)/(1+exp(-I(j)2); end for i=1:1:2 for j=1:1:6 dw1(i,j)=e(k)*xite*FI(j)*w2(j)*x(i); % dw1 calculation end end w1=w1_1+dw1+alfa*(w1_1-w1_2); % rectify of w1 % jacobian information yu=0; for j=1:1:6 yu=yu+w2(j)*w1(1,j)*FI(j); end dyu(k)=yu; 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);figure(2);plot(time,y-yn,r);xlabel(times);ylabel(error);figure(3);plot(time,dyu);xlabel(times);ylabel(dyu);运行结果为：（2） 采用RBF网络仿真 网路结构为2-4-1，采样时间1ms，输入信号，权值的初值随机取值，高斯基函数初值，。仿真m文件程序如下：%RBF simulationclear allclear allalfa=0.05;xite=0.5;x=0,0;b=1.5*ones(4,1);c=0.5*ones(2,4);w=rands(4,1);w_1=w;w_2=w_1;c_1=c;c_2=c_1;b_1=b;b_2=b_1d_w=0*w;d_b=0*b;y_1=0;ts=0.001;for k=1:1:2000; time(k)=k*ts; u(k)=0.5*sin(1*2*pi*k*ts); y(k)=(u(k)-0.9*y_1)/(1+y_12); x(1)=u(k); x(2)=y_1; for j=1:1:4 h(j)=exp(-norm(x-c(:,j)2/(2*b(j)*b(j); end ym(k)=w*h; em(k)=y(k)-ym(k); for j=1:1:4 d_w(j)=xite*em(k)*h(j); d_b(j)=xite*em(k)*w(j)*h(j)*(b(j)-3)*norm(x-c(:,j)2; for i=1:1:2 d_c(i,j)=xite*em(k)*w(j)*h(j)*(x(i)-c(i,j)*(b(j)-2); end end w=w_1+d_w+alfa*(w_1-w_1); b=b_1+d_b+alfa*(b_1-b_2); c=c_1+d_c+alfa*(c_1-c_2); % Jacobian information yu=0; for j=1:1:4 yu=yu+w(j)*h(j)*(c(1,j)-x(1)/b(j)2; end dyu(k)=yu; y_1=y(k); w_2=w_1; w_1=w; c_2=c_1; c_1=c; b_2=b_1; b_1=b; endfigure(1);plot(time,y,r,time,ym,b);xlabel(time(s);ylabel(y and ym);figure(2);plot(time,y-ym,r);xlabel(time(s);ylabel(error);figure(3);plot(time,dyu,b);xlabel(time(s);ylabel(dyu);仿真结果为：（3） DRNN网路仿真采样时间1ms，输入信号，权值的初值随机取值，取。仿真m文件程序为：%DRNN simulationclear all;clear all;wd=rands(7,1);wo=rands(7,1);wi=rands(3,7);xj=zeros(7,1);xj_1=xj;u_1=0;y_1=0;xitei=0.35;xited=0.35;xiteo=0.35;ts=0.001;for k=1:1:1000 time(k)=k*ts; u(k)=0.5*sin(4*pi*k*ts); y(k)=(u_1-0.9*y_1)/(1+y_12); Ini=u_1,y_1,1; for j=1:1:7 sj(j)=Ini*wi(:,j)+wd(j)*xj(j); end for j=1:1:7 xj(j)=(1-exp(-sj(j)/(1+exp(-sj(j); end Pj=0*xj; for j=1:1:7 Pj=wo(j)*(1+xj(j)*(1-xj(j)*xj_1(j); end Qij=0*wi; for j=1:1:7 for i=1:1:3 Qij(i,j)=wo(j)*(1+xj(j)*(1-xj(j)*Ini(i); end end ymk=0; for j=1:1:7 ymk=ymk+xj(j)*wo(j); end ym(k)=ymk; e(k)=y(k)-ym(k); wo=wo+xiteo*e(k)*xj; wd=wd+xited*e(k)*Pj; wi=wi+xitei*e(k)*Qij; xj_1=xj