clc;

%----------------------------

%单轨迹预测input

c0=0.5;

c1=0.2;

c2=0.3;

c3=0.4;

y=@(x)c0+c1*x+c2*x.^2+c3*x.^3;

x=0.1:0.2:30;

% plot(x,y(x),'r-');

%----------------------

x1=0.1:0.2:6;

tar1=y(x1);

x2=6.2:0.2:12;

tar2=y(x2);

x3=12.2:0.2:18;

tar3=y(x3);

x4=18.2:0.2:24;

tar4=y(x4);

x5=24.2:0.2:30;

tar5=y(x5);

%-------------------------

X=[x1;x3;x5;x2;x4];

Y=[tar1;tar3;tar5;tar2;tar4];

%----------

%归一化

% M=max(max(X));

% N=max(max(Y));

% Q=max(M,N);

% X=X/Q;

% Y=Y/Q;

% A=zeros(30,2);

% B=repmat(A,1,5);

%-------------------------

%input%

Xi={1,5};%输入对象单元为(X,Y)

%----------------------------

for j=1:5

inputbuff=zeros(30,2);

for i=1:30;

inputbuff(i,1)=X(1,i);

inputbuff(i,2)=Y(1,i);

end

Xi{1,j}=inputbuff;

end

%Xi=Xi';%cell 5 X 1---array 30 X 2

%----------------------

%target%

tx=40:0.3:42.7;

ty=y(tx);

Yt=zeros(10,2);

for k=1:10

Yt(k,1)=tx(1,k);

Yt(k,2)=ty(1,k);

end

MM=max(max(Yt));

% Yt=Yt/MM;

%YYt={Yt};%cell 1X1---array 10 X 2

%--------------------------

tt1(1,:)=Yt(1,:);

tt1(2,:)=Yt(2,:);

tt2(1,:)=Yt(3,:);

tt2(2,:)=Yt(4,:);

tt3(1,:)=Yt(5,:);

tt3(2,:)=Yt(6,:);

tt4(1,:)=Yt(7,:);

tt4(2,:)=Yt(8,:);

tt5(1,:)=Yt(9,:);

tt5(2,:)=Yt(10,:);

YYt={tt1,tt3,tt5,tt2,tt4};%cell 1X5---array 2 X 2

%-------------------------------------------------

bpnet=newff(Xi,YYt,12,{'logsig', 'purelin'}, 'traingdx', 'learngdm');

view(bpnet);

%建立BP神经网络， 个隐层神经元，个输出神经元

%tranferFcn属性 'logsig' 隐层采用Sigmoid传输函数

%tranferFcn属性 'logsig' 输出层采用Sigmoid传输函数

%trainFcn属性 'traingdx' 自适应调整学习速率附加动量因子梯度下降反向传播算法训练函数

%learn属性 'learngdm' 附加动量因子的梯度下降学习函数

net.trainParam.epochs=1000;%允许最大训练步数1000步

net.trainParam.goal=0.001; %训练目标最小误差0.001

net.trainParam.show=100; %每间隔100步显示一次训练结果

net.trainParam.lr=0.05; %学习速率0.05

[bpnet,tr]=train(bpnet,Xi,YYt);

%------------------------------------------------

%testinput%

Test={1};

xt=0.2:0.2:6;

yt=y(xt);

%------------------

testbuff=zeros(30,2);

for ii=1:30;

testbuff(ii,1)=xt(1,ii);

testbuff(ii,2)=yt(1,ii);

end

% testbuff=testbuff/Q;

Test{1,1}=testbuff;

%------------------------

T=sim(bpnet,Test);

% out=T{1}*MM;