hw6_3_6243_2003 - % simulation u(:,t+1)=du(:,t1);

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function hw6_3_6243_2003(x0,x1) % function hw6_3_6243_2003(x0,x1) % % moving the state of system % x1'=cos(x3)u1 % x2'=sin(x3)u1 % x3'=x4*u1 % x4'=u2 % from x0 to x1 (default: randomly generated) if nargin<2, x1=0.5*randn(4,1); end if nargin<1, x0=0.5*randn(4,1); end dt=0.01; % simulation step tol=0.01; % positioning accuracy N=4000; % maximal number of steps x=zeros(4,N); % to keep the state values u=zeros(2,N); % to keep the control values kk=zeros(1,N); % to keep strategies t=1; % current time x(:,t)=x0(:); x1=x1(:); while t<N, % g=[g1 g2 g3 g4] g=[cos(x(3,t)) 0 0 -sin(x(3,t));sin(x(3,t)) 0 0 cos(x(3,t));x(4,t) 0 1 0;0 1 0 0]; v=g'*(x1-x(:,t))./[(1+x(4,t)^2);1;1;1]; % normalzation if any(abs(v)>tol), [y,k]=max(abs(v)); du=S(k,v(k)); else du=zeros(2,N-t); end for t1=1:min(size(du,2),N-t),
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Unformatted text preview: % simulation u(:,t+1)=du(:,t1); x(:,t+1)=x(:,t)+dt*[cos(x(3,t)) 0;sin(x(3,t)) 0;x(4,t) 0;0 1]*u(:,t+1); kk(t+1)=k; t=t+1; end end tt=dt*(0:N-1); close(gcf) for k=1:4, subplot(5,1,k); plot(tt,x(k,:),tt,x1(k)); grid end subplot(5,1,5);plot(tt,0.9*kk);grid; function u=S(k,v) % control needed to implement the differential flow for m steps along gk dt=0.01; switch k, case 1, m=sign(v)*(floor(abs(v)/dt)+1); u=[repmat(sign(m),1,abs(m));zeros(1,abs(m))]; case 2, m=sign(v)*(floor(abs(v)/dt)+1); u=[zeros(1,abs(m));repmat(sign(m),1,abs(m))]; case 3, v1=sign(v)*sqrt(abs(v)); u=[S(2,v1) S(1,abs(v1)) S(2,-v1) S(1,-abs(v1))]; case 4, v1=sign(v)*sqrt(abs(v)); u=[S(3,v1) S(1,abs(v1)) S(3,-v1) S(1,-abs(v1))]; end...
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This note was uploaded on 11/07/2011 for the course AERO 16.36 taught by Professor Alexandremegretski during the Spring '09 term at MIT.

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hw6_3_6243_2003 - % simulation u(:,t+1)=du(:,t1);

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