基于模型逼近的N关节机械臂神经网络自适应控制matlab仿真程序

function [sys,x0,str,ts] = spacemodel(t,x,u,flag) switch flag, case 0, [sys,x0,str,ts]=mdlInitializeSizes; case 1, sys=mdlDerivatives(t,x,u); case 3, sys=mdlOutputs(t,x,u); case {2,4,9} sys=[]; otherwise error(['Unhandled flag = ',num2str(flag)]); end function [sys,x0,str,ts]=mdlInitializeSizes global node c b Fai node=7; c=0.1*[-1.5 -1 -0.5 0 0.5 1 1.5; -1.5 -1 -0.5 0 0.5 1 1.5; -1.5 -1 -0.5 0 0.5 1 1.5; -1.5 -1 -0.5 0 0.5 1 1.5; -1.5 -1 -0.5 0 0.5 1 1.5]; b=10; Fai=5*eye(2); sizes = simsizes; sizes.NumContStates = 2*node; sizes.NumDiscStates = 0; sizes.NumOutputs = 3; sizes.NumInputs = 11; sizes.DirFeedthrough = 1; sizes.NumSampleTimes = 0; sys = simsizes(sizes); x0 = 0.1*ones(1,2*node); str = []; ts = []; function sys=mdlDerivatives(t,x,u) global node c b Fai qd1=u(1); d_qd1=u(2); dd_qd1=u(3); qd2=u(4); d_qd2=u(5); dd_qd2=u(6); q1=u(7); d_q1=u(8); q2=u(9); d_q2=u(10); q=[q1;q2]; e1=qd1-q1; e2=qd2-q2; de1=d_qd1-d_q1; de2=d_qd2-d_q2; e=[e1;e2]; de=[de1;de2]; r=de+Fai*e; qd=[qd1;qd2]; dqd=[d_qd1;d_qd2]; dqr=dqd+Fai*e; ddqd=[dd_qd1;dd_qd2]; ddqr=ddqd+Fai*de; z1=[e(1);de(1);qd(1);dqd(1);ddqd(1)]; z2=[e(2);de(2);qd(2);dqd(2);ddqd(2)]; for j=1:1:node h1(j)=exp(-norm(z1-c(:,j))^2/(b*b)); h2(j)=exp(-norm(z2-c(:,j))^2/(b*b)); end F=15*eye(node); for i=1:1:node sys(i)=15*h1(i)*r(1); sys(i+node)=15*h2(i)*r(2); end function sys=mdlOutputs(t,x,u) global node c b Fai qd1=u(1); d_qd1=u(2); dd_qd1=u(3); qd2=u(4); d_qd2=u(5); dd_qd2=u(6); q1=u(7); d_q1=u(8); q2=u(9); d_q2=u(10); q=[q1;q2]; e1=qd1-q1; e2=qd2-q2; de1=d_qd1-d_q1; de2=d_qd2-d_q2; e=[e1;e2]; de=[de1;de2]; r=de+Fai*e; qd=[qd1;qd2]; dqd=[d_qd1;d_qd2]; dqr=dqd+Fai*e; ddqd=[dd_qd1;dd_qd2]; ddqr=ddqd+Fai*de; z=[e;de;qd;dqd;ddqd]; W_f1=[x(1:node)]'; W_f2=[x(node+1:node*2)]'; z1=[e(1);de(1);qd(1);dqd(1);ddqd(1)]; z2=[e(2);de(2);qd(2);dqd(2);ddqd(2)]; for j=1:1:node h1(j)=exp(-norm(z1-c(:,j))^2/(b*b)); h2(j)=exp(-norm(z2-c(:,j))^2/(b*b)); end fn=[W_f1*h1'; W_f2*h2']; Kv=20*eye(2); epN=0.20;bd=0.1; v=-(epN+bd)*sign(r); tol=fn+Kv*r-0.45*v; fn_norm=norm(fn); sys(1)=tol(1); sys(2)=tol(2); sys(3)=fn_norm;