H-infinity LQ gain (full state)
[K,X,err]=leqr(P12,Vx)
:P12 syslin list : :Vx symmetric nonnegative matrix (should be small enough) : :K,X two real matrices : :err a real number (l1 norm of LHS of Riccati equation) :
leqr computes the linear suboptimal H-infinity LQ full-state gain for the plant P12=[A,B2,C1,D12] in continuous or discrete time.
P12 is a syslin list (e.g. P12=syslin(‘c’,A,B2,C1,D12)).
[C1' ] [Q S]
[ ] * [C1 D12] = [ ]
[D12'] [S' R]
Vx is related to the variance matrix of the noise w perturbing x; (usually Vx=gama^-2*B1*B1’).
The gain K is such that A + B2*K is stable.
X is the stabilizing solution of the Riccati equation.
For a continuous plant:
(A-B2*`inv`_(R)*S')'*X+X*(A-B2*`inv`_(R)*S')-X*(B2*`inv`_(R)*B2'-Vx)*X+Q-S*`inv`_(R)*S'=0
K=-`inv`_(R)*(B2'*X+S)
For a discrete time plant:
X-(Abar'*`inv`_((`inv`_(X)+B2*`inv`_(R)*B2'-Vx))*Abar+Qbar=0
K=-`inv`_(R)*(B2'*`inv`_(`inv`_(X)+B2*`inv`_(R)*B2'-Vx)*Abar+S')
with Abar=A-B2*inv(R)*S’ and Qbar=Q-S*inv(R)*S’
The 3-blocks matrix pencils associated with these Riccati equations are:
discrete continuous
|I -Vx 0| | A 0 B2| |I 0 0| | A Vx B2|
z|0 A' 0| - |-Q I -S| s|0 I 0| - |-Q -A' -S |
|0 B2' 0| | S' 0 R| |0 0 0| | S' -B2' R|