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📋📋📋本文目录如下:🎁🎁🎁
目录
💥1 概述
📚2 运行结果
🌈3 Matlab代码实现
🎉4 参考文献
💥1 概述
上一次降落一个比较简单的:
基于BP神经网络的轨迹跟踪(Matlab代码实现)
📚2 运行结果
🌈3 Matlab代码实现
部分代码:
for k=1:1:50000
%时间
time(k)=k*ts;
%% 输入层
%输入正弦值
u(k)=sin(0.1*k*ts);
y(k)=u(k)+y_1/(1+y_1^2);
x=[u(k),y(k)]'; % Layer1:input
y1=x;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% 模糊化层
for i=1:1:2 % Layer2:fuzzation
for ii=1:1:5
net2(i,ii)=-(y1(i)-c(i,ii))^2/bj^2;
end
end
for i=1:1:2
for ii=1:1:5
y2(i,ii)=exp(net2(i,ii));
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% 模糊推理层
for ii=1:1:5 % Layer3:fuzzy inference(49 rules)
m1(ii)=y2(1,ii);
m2(ii)=y2(2,ii);
end
for i=1:1:5
for ii=1:1:5
y3(i,ii)=m2(i)*m1(ii);
end
end
for k=1:1:50000
%时间
time(k)=k*ts;
%% 输入层
%输入正弦值
u(k)=sin(0.1*k*ts);
y(k)=u(k)+y_1/(1+y_1^2);
x=[u(k),y(k)]'; % Layer1:input
y1=x;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% 模糊化层
for i=1:1:2 % Layer2:fuzzation
for ii=1:1:5
net2(i,ii)=-(y1(i)-c(i,ii))^2/bj^2;
end
end
for i=1:1:2
for ii=1:1:5
y2(i,ii)=exp(net2(i,ii));
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% 模糊推理层
for ii=1:1:5 % Layer3:fuzzy inference(49 rules)
m1(ii)=y2(1,ii);
m2(ii)=y2(2,ii);
end
for i=1:1:5
for ii=1:1:5
y3(i,ii)=m2(i)*m1(ii);
end
end
🎉4 参考文献
部分理论来源于网络,如有侵权请联系删除。
[1]缸明义,夏兴国,张庆丰,吴彩林.基于模糊神经网络的机械手轨迹跟踪控制系统[J].江汉大学学报(自然科学版),2021,49(01):66-73.DOI:10.16389/j.cnki.cn42-1737/n.2021.01.010.