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See the recommended documentation of this function
lqg2stan
LQG to standard problem
Syntax
[P_aug, r] = lqg2stan(P, Qxu, Qwv)
Arguments
- P
 State space representation of the nominal plant (
nuinputs,nyoutputs,nxstates).- Qxu
 [Q, S ; S', N]symmetricnx+nubynx+nuweighting matrix.- Qwv
 [R,T;T',V]symmetricnx+nybynx+nycovariance matrix.- r
 Row vector
[ny nu].- P_aug
 Augmented plant state space representation (see: syslin)
Description
lqg2stan returns the augmented plant for linear LQG (H2) controller
            design problem defined by:
The nominal plant
P: described by
The (instantaneous) cost function
.The noises covariance matrix
![\mathbb{E}(\left[\begin{array}{l}w\\v\end{array}\right]
              \left[\begin{array}{ll}w](/docs/6.1.1/en_US/_LaTeX_lqg2stan.xml_3.png)

Algorithm
If [B1; D21] is a factor of
            Qxu, [C1, D12] is a
            factor of Qwv (see: fullrf) then
P_aug = syslin(P.dt, P.A, [B1,P.B], [C1;-P.C], [0,D12;D21,P.D])
Examples
ny = 2; nu = 3; nx = 4; P = ssrand(ny,nu,nx); Qxu = rand(nx+nu,nx+nu); Qxu = Qxu * Qxu'; Qwv = rand(nx+ny,nx+ny); Qwv = Qwv * Qwv'; [P_aug, r] = lqg2stan(P, Qxu, Qwv); K = lqg(P_aug,r); // K=LQG-controller spec(h_cl(P_aug, r, K)) // Closed loop should be stable //Same as Cl = P/.K; spec(Cl('A')) lqg2stan(1/(%s+2), eye(2,2), eye(2,2))
See also
- lqg — LQG compensator
 - lqr — LQ compensator (full state)
 - lqe — linear quadratic estimator (Kalman Filter)
 - obscont — observer based controller
 - h_inf — Continuous time H-infinity (central) controller
 - augment — augmented plant
 - fstabst — Youla's parametrization of continuous time linear dynamical systems
 - feedback — feedback operation
 
History
| Version | Description | 
| 6.0 | It is no longer necessary to enter -P to get P_aug
            instead of -P_aug
            (bug 13751 fixed). | 
| Report an issue | ||
| << lqg | Linear Quadratic | lqg_ltr >> |