Man Scilab

obscont
Scilab Function

obscont - observer based controller

Calling Sequence

[K]=obscont(P,Kc,Kf)
[J,r]=obscont(P,Kc,Kf)

Parameters

Description

obscont returns the observer-based controller associated with a nominal plant P with matrices [A,B,C,D] ( syslin list).

The full-state control gain is Kc and the filter gain is Kf . These gains can be computed, for example, by pole placement.

A+B*Kc and A+Kf*C are (usually) assumed stable.

K is a state-space representation of the compensator K: y->u in:

xdot = A x + B u, y=C x + D u, zdot= (A + Kf C)z -Kf y +B u, u=Kc z

K is a linear system ( syslin list) with matrices given by: K=[A+B*Kc+Kf*C+Kf*D*Kc,Kf,-Kc] .

The closed loop feedback system Cl: v ->y with (negative) feedback K (i.e. y = P u, u = v - K y , or xdot = A x + B u, y = C x + D u, zdot = (A + Kf C) z - Kf y + B u, u = v -F z ) is given by Cl = P/.(-K)

The poles of Cl ( spec(cl('A')) ) are located at the eigenvalues of A+B*Kc and A+Kf*C .

Invoked with two output arguments obscont returns a (square) linear system K which parametrizes all the stabilizing feedbacks via a LFT.

Let Q an arbitrary stable linear system of dimension r(2) x r(1) i.e. number of inputs x number of outputs in P . Then any stabilizing controller K for P can be expressed as K=lft(J,r,Q) . The controller which corresponds to Q=0 is K=J(1:nu,1:ny) (this K is returned by K=obscont(P,Kc,Kf) ). r is size(P) i.e the vector [number of outputs, number of inputs];

Examples


ny=2;nu=3;nx=4;P=ssrand(ny,nu,nx);[A,B,C,D]=abcd(P);
Kc=-ppol(A,B,[-1,-1,-1,-1]);  //Controller gain
Kf=-ppol(A',C',[-2,-2,-2,-2]);Kf=Kf';    //Observer gain
cl=P/.(-obscont(P,Kc,Kf));spec(cl('A'))   //closed loop system
[J,r]=obscont(P,Kc,Kf);
Q=ssrand(nu,ny,3);Q('A')=Q('A')-(maxi(real(spec(Q('A'))))+0.5)*eye(Q('A')) 
//Q is a stable parameter
K=lft(J,r,Q);
spec(h_cl(P,K))  // closed-loop A matrix (should be stable);
 
  

See Also

ppol ,   lqg ,   lqr ,   lqe ,   h_inf ,   lft ,   syslin ,   feedback ,   observer ,  

Author

F.D. ; ;

Back