bp-nn.m

用BP神经网络实现模糊控制规则为T=int[(e +ec)/2]的模糊神经网络控制器。可以改变隐层节点数和学习速率。网络训练算法是变学习速率法。

P=[-2 -2 -2 -2 -2 -1 -1 -1 -1 -1 0 0 0 0 0 1 1 1 1 1 2 2 2 2 2;
   -2 -1 0 1 2 -2 -1 0 1 2 -2 -1 0 1 2 -2 -1 0 1 2 -2 -1 0 1 2];
T=[-2 -1 -1 0 0 -1 -1 0 0 0 -1 0 0 0 1 0 0 0 1 1 0 0 1 1 2];
[R,Q]=size(P); 
[S2,Q]=size(T);
S1=5;
[W1]=rands(S1,R);
[B1]=rands(S1,Q);
[W2,B2]=rands(S2,S1);

net=newcf(minmax(P),[5,1],{'tansig','purelin'},'traingda');
net.trainParam.goal=0.001;
net.trainParam.Ir=0.005;
net.trainParam.Ir_inc=1.04;
net.trainParam.Ir_dec=0.8;
net.trainParam.epochs=20000;
tic
[net,tr]=train(net,P,T);
toc
Y=sim(net,P)