Scilab Reference Manual |
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gfrancis — Francis equations for tracking
[L,M,T]=gfrancis(Plant,Model)
Given the the linear plant:
x'= F*x + G*u y = H*x + J*u
and the linear model
xm'= A*xm + B*um ym = C*xm + D*um
the goal is for the plant to track the model i.e. e = y - ym ---> 0 while keeping stable the state x(t) of the plant. u is given by feedforward and feedback
u = L*xm + M*um + K*(x-T*xm) = [K , L-K*T] *(x,xm) + M*um
The matrices T,L,M satisfy generalized Francis equations
F*T + G*L = T*A H*T + J*L = C G*M = T*B J*M = D
The matrix K must be chosen as stabilizing the pair (F,G) See example of use in directory demos/tracking.
Plant=ssrand(1,3,5); [F,G,H,J]=abcd(Plant); nw=4;nuu=2;A=rand(nw,nw); st=maxi(real(spec(A)));A=A-st*eye(A); B=rand(nw,nuu);C=2*rand(1,nw);D=0*rand(C*B); Model=syslin('c',A,B,C,D); [L,M,T]=gfrancis(Plant,Model); norm(F*T+G*L-T*A,1) norm(H*T+J*L-C,1) norm(G*M-T*B,1) norm(J*M-D,1)
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