SciPy

scipy.linalg.solve_discrete_are

scipy.linalg.solve_discrete_are(a, b, q, r, e=None, s=None, balanced=True)[source]

Solves the discrete-time algebraic Riccati equation (DARE).

The DARE is defined as

\[A^HXA - X - (A^HXB) (R + B^HXB)^{-1} (B^HXA) + Q = 0\]

The limitations for a solution to exist are :

  • All eigenvalues of \(A\) outside the unit disc, should be controllable.
  • The associated symplectic pencil (See Notes), should have eigenvalues sufficiently away from the unit circle.

Moreover, if e and s are not both precisely None, then the generalized version of DARE

\[A^HXA - E^HXE - (A^HXB+S) (R+B^HXB)^{-1} (B^HXA+S^H) + Q = 0\]

is solved. When omitted, e is assumed to be the identity and s is assumed to be the zero matrix.

Parameters:

a : (M, M) array_like

Square matrix

b : (M, N) array_like

Input

q : (M, M) array_like

Input

r : (N, N) array_like

Square matrix

e : (M, M) array_like, optional

Nonsingular square matrix

s : (M, N) array_like, optional

Input

balanced : bool

The boolean that indicates whether a balancing step is performed on the data. The default is set to True.

Returns:

x : (M, M) ndarray

Solution to the discrete algebraic Riccati equation.

Raises:

LinAlgError

For cases where the stable subspace of the pencil could not be isolated. See Notes section and the references for details.

See also

solve_continuous_are
Solves the continuous algebraic Riccati equation

Notes

The equation is solved by forming the extended symplectic matrix pencil, as described in [R126], \(H - \lambda J\) given by the block matrices

[  A   0   B ]             [ E   0   B ]
[ -Q  E^H -S ] - \lambda * [ 0  A^H  0 ]
[ S^H  0   R ]             [ 0 -B^H  0 ]

and using a QZ decomposition method.

In this algorithm, the fail conditions are linked to the symmetry of the product \(U_2 U_1^{-1}\) and condition number of \(U_1\). Here, \(U\) is the 2m-by-m matrix that holds the eigenvectors spanning the stable subspace with 2m rows and partitioned into two m-row matrices. See [R126] and [R127] for more details.

In order to improve the QZ decomposition accuracy, the pencil goes through a balancing step where the sum of absolute values of \(H\) and \(J\) rows/cols (after removing the diagonal entries) is balanced following the recipe given in [R128]. If the data has small numerical noise, balancing may amplify their effects and some clean up is required.

New in version 0.11.0.

References

[R126](1, 2, 3) P. van Dooren , “A Generalized Eigenvalue Approach For Solving Riccati Equations.”, SIAM Journal on Scientific and Statistical Computing, Vol.2(2), DOI: 10.1137/0902010
[R127](1, 2) A.J. Laub, “A Schur Method for Solving Algebraic Riccati Equations.”, Massachusetts Institute of Technology. Laboratory for Information and Decision Systems. LIDS-R ; 859. Available online : http://hdl.handle.net/1721.1/1301
[R128](1, 2) P. Benner, “Symplectic Balancing of Hamiltonian Matrices”, 2001, SIAM J. Sci. Comput., 2001, Vol.22(5), DOI: 10.1137/S1064827500367993