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lqg2stan
LQG to standard problem
Syntax
[P_aug, r] = lqg2stan(P, Qxu, Qwv)
Arguments
- P
State space representation of the nominal plant (
nu
inputs,ny
outputs,nx
states).- Qxu
[Q, S ; S', N]
symmetricnx+nu
bynx+nu
weighting matrix.- Qwv
[R,T;T',V]
symmetricnx+ny
bynx+ny
covariance 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 byThe (instantaneous) cost function .
The noises covariance matrix
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 | ||
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