(Not recommended) Continuous-time algebraic Riccati equation solution
care
is not recommended. Use icare
instead. For more information, see Compatibility Considerations.
[X,L,G] = care(A,B,Q)
[X,L,G] = care(A,B,Q,R,S,E)
[X,L,G,report] = care(A,B,Q,...)
[X1,X2,D,L] = care(A,B,Q,...,'factor')
[X,L,G] = care(A,B,Q)
computes the unique solution
X
of the continuous-time algebraic Riccati equation
The care
function also returns the gain matrix, .
[X,L,G] = care(A,B,Q,R,S,E)
solves the more general Riccati
equation
When omitted, R
, S
, and E
are
set to the default values R=I
, S=0
, and
E=I
. Along with the solution X
,
care
returns the gain matrix and a vector L
of closed-loop eigenvalues, where
L=eig(A-B*G,E)
[X,L,G,report] = care(A,B,Q,...)
returns a diagnosis
report
with:
This syntax does not issue any error message when X fails to exist.
[X1,X2,D,L] = care(A,B,Q,...,'factor')
returns two matrices
X1
, X2
and a diagonal scaling matrix
D
such that X = D*(X2/X1)*D
.
The vector L contains the closed-loop eigenvalues. All outputs are empty when the associated Hamiltonian matrix has eigenvalues on the imaginary axis.
Solve Algebraic Riccati Equation
Given
you can solve the Riccati equation
by
a = [-3 2;1 1] b = [0 ; 1] c = [1 -1] r = 3 [x,l,g] = care(a,b,c'*c,r)
This yields the solution
x x = 0.5895 1.8216 1.8216 8.8188
You can verify that this solution is indeed stabilizing by comparing the
eigenvalues of a
and a-b*g
.
[eig(a) eig(a-b*g)] ans = -3.4495 -3.5026 1.4495 -1.4370
Finally, note that the variable l
contains the closed-loop
eigenvalues eig(a-b*g)
.
l l = -3.5026 -1.4370
Solve H-infinity ()-like Riccati Equation
To solve the -like Riccati equation
rewrite it in the care
format as
You can now compute the stabilizing solution by
B = [B1 , B2] m1 = size(B1,2) m2 = size(B2,2) R = [-g^2*eye(m1) zeros(m1,m2) ; zeros(m2,m1) eye(m2)] X = care(A,B,C'*C,R)
The pair must be stabilizable (that is, all unstable modes are controllable). In addition, the associated Hamiltonian matrix or pencil must have no eigenvalue on the imaginary axis. Sufficient conditions for this to hold are detectable when and , or
care
implements the algorithms described in [1]. It works with the Hamiltonian matrix when R is well-conditioned and ; otherwise it uses the extended Hamiltonian pencil and QZ
algorithm.
[1] Arnold, W.F., III and A.J. Laub, "Generalized Eigenproblem Algorithms and Software for Algebraic Riccati Equations," Proc. IEEE®, 72 (1984), pp. 1746-1754