用于自适应控制的模糊神经网络代码，输入是误差和误差变化率.7z

%FNN arithmatic program %.-------init-----------------? d=1.8; %input k=1; %b_1=exp(-8*.001)+exp(-6*.001); %b_2=exp(-14*.001) ; %b_3=exp(-6*.001)-exp(-8*.001); e(1)=d; ee(1)=0; m=[-3 -1.5 0 1.5 3;-2 -1 0 1 2]; q=[.6 .6 .6 .6 .6;.4 .4 .4 .4 .4]; o=[-3 -3 -3 -3 -3;0 -1.5 -1.5 -1.5 -3;3 1.5 0 -1.5 -3;3 3 1.5 1.5 1.5;3 3 3 3 3]; %o=[0 0 0 0 0;0 0 0 0 0;0 0 0 0 0;0 0 0 0 0;0 0 0 0 0]; d_o_1=zeros(size(o)); %learning rate self-adaptive; d_m_1=zeros(size(m)); d_q_1=zeros(size(q)); n_m =.05*ones(size(m)); n_q =.05*ones(size(q)); n_o= 0.01*ones(size(o)); %-----------process_1--------------------- while k<250 net1=[e(k) ee(k)]; y1=net1; %-----------Process_2--------------------- for i=1:2 for j=1:5 net2(i,j)=y1(i); y2(i,j)=exp(-(net2(i,j)-m(i,j))^2/q(i,j)^2); end end %-----------process_3---------------- sum_3=0; for i=1:5 for j=1:5 net3(i,j)=y2(1,i)*y2(2,j); sum_3=sum_3+net3(i,j); end end for i=1:5 for j=1:5 y3(i,j)=net3(i,j); end end %------------Process_4- -----------------? net4=0; for i=1:5 for j=1:5 net4=net4+o(i,j)*y3(i,j); end end y4(k)=net4/sum_3; %------------Process_object-------------- %T(1)=0; %T(2)=5*b_3*y4(1)/b_2; %sum_out=0; %if k>1 % for i=1:k % sum_out=sum_out+y4(i); % end % T(k+1)=(1*b_3*sum_out+0.5*b_1*T(k)-T(k-1))/b_2; %end %--------------study_Process_4&3---------------------? d4(1)=0; d4(k)=(1.8-y4(k)) e(k+1)=d-y4(k); ee(k+1)=e(k+1)-e(k); for i=1:5 for j=1:5 d_o(i,j)=d4(k)*y3(i,j); d3(i,j)=d4(k)*o(i,j) ; end end %--------------study_process_2------------------- d2=zeros(size(y2)); for j=1:5 for i=1:5 d2(1,j)=d2(1,j)+d3(j,i)*y2(2,i)*y2(1,j); d2(2,j)=d2(2,j)+d3(i,j)*y2(1,i)*y2(2,j) ; end end for i=1:2 for j=1:5 d_m(i,j)=d2(i,j)*2*(y1(i)-m(i,j))/q(i,j)^2; d_q(i,j)=d2(i,j)*2*(y1(i)-m(i,j))^2/q(i,j)^3; end end %--------------modify parameters-----------------? for i=1:2 for j=1:5 f_m(i,j)=sign(d_m(i,j)*d_m_1(i,j)); f_q(i,j)=sign(d_q(i,j)*d_q_1(i,j)); n_m(i,j)=2^f_m(i,j)*n_m(i,j); n_q(i,j)=2^f_q(i,j)*n_q(i,j); m(i,j)=m(i,j)+n_m(i,j)*d_m(i,j); q(i,j)=q(i,j)+n_q(i,j)*d_q(i,j); d_m_1(i,j)=d_m(i,j); d_q_1(i,j)=d_q(i,j); end end for i=1:5 for j=1:5 f_o(i,j)=sign(d_o(i,j)*d_o_1(i,j)); n_o(i,j)=1.1^f_o(i,j)*n_o(i,j); o(i,j)=o(i,j)+n_o(i,j)*d_o(i,j); d_o_1(i,j)=d_o(i,j); end end k=k+1; end