SB02MU - SLICOT Library Routine Documentation

## SB02MU

### Constructing the 2n-by-2n Hamiltonian or symplectic matrix for linear-quadratic optimization problems

[Specification] [Arguments] [Method] [References] [Comments] [Example]

Purpose

      To construct the 2n-by-2n Hamiltonian or symplectic matrix S
      associated to the linear-quadratic optimization problem, used to
      solve the continuous- or discrete-time algebraic Riccati equation,
      respectively.

      For a continuous-time problem, S is defined by

              (  A  -G )
          S = (        ),                                       (1)
              ( -Q  -A')

      and for a discrete-time problem by

                  -1       -1
              (  A        A  *G     )
          S = (   -1           -1   ),                          (2)
              ( QA     A' + Q*A  *G )

      or

                        -T         -T
              (  A + G*A  *Q   -G*A   )
          S = (      -T            -T ),                        (3)
              (    -A  *Q         A   )

      where A, G, and Q are N-by-N matrices, with G and Q symmetric.
      Matrix A must be nonsingular in the discrete-time case.

Specification

          SUBROUTINE SB02MU( DICO, HINV, UPLO, N, A, LDA, G, LDG, Q, LDQ, S,
         $                   LDS, IWORK, DWORK, LDWORK, INFO )
    C     .. Scalar Arguments ..
          CHARACTER         DICO, HINV, UPLO
          INTEGER           INFO, LDA, LDG, LDQ, LDS, LDWORK, N
    C     .. Array Arguments ..
          INTEGER           IWORK(*)
          DOUBLE PRECISION  A(LDA,*), DWORK(*), G(LDG,*), Q(LDQ,*),
         $                  S(LDS,*)

Arguments

Mode Parameters

      DICO    CHARACTER*1
              Specifies the type of the system as follows:
              = 'C':  Continuous-time system;
              = 'D':  Discrete-time system.

      HINV    CHARACTER*1
              If DICO = 'D', specifies which of the matrices (2) or (3)
              is constructed, as follows:
              = 'D':  The matrix S in (2) is constructed;
              = 'I':  The (inverse) matrix S in (3) is constructed.
              HINV is not referenced if DICO = 'C'.

      UPLO    CHARACTER*1
              Specifies which triangle of the matrices G and Q is
              stored, as follows:
              = 'U':  Upper triangle is stored;
              = 'L':  Lower triangle is stored.

Input/Output Parameters

      N       (input) INTEGER
              The order of the matrices A, G, and Q.  N >= 0.

      A       (input/output) DOUBLE PRECISION array, dimension (LDA,N)
              On entry, the leading N-by-N part of this array must
              contain the matrix A.
              On exit, if DICO = 'D', and INFO = 0, the leading N-by-N
                                                      -1
              part of this array contains the matrix A  .
              Otherwise, the array A is unchanged on exit.

      LDA     INTEGER
              The leading dimension of array A.  LDA >= MAX(1,N).

      G       (input) DOUBLE PRECISION array, dimension (LDG,N)
              The leading N-by-N upper triangular part (if UPLO = 'U')
              or lower triangular part (if UPLO = 'L') of this array
              must contain the upper triangular part or lower triangular
              part, respectively, of the symmetric matrix G.
              The strictly lower triangular part (if UPLO = 'U') or
              strictly upper triangular part (if UPLO = 'L') is not
              referenced.

      LDG     INTEGER
              The leading dimension of array G.  LDG >= MAX(1,N).

      Q       (input) DOUBLE PRECISION array, dimension (LDQ,N)
              The leading N-by-N upper triangular part (if UPLO = 'U')
              or lower triangular part (if UPLO = 'L') of this array
              must contain the upper triangular part or lower triangular
              part, respectively, of the symmetric matrix Q.
              The strictly lower triangular part (if UPLO = 'U') or
              strictly upper triangular part (if UPLO = 'L') is not
              referenced.

      LDQ     INTEGER
              The leading dimension of array Q.  LDQ >= MAX(1,N).

      S       (output) DOUBLE PRECISION array, dimension (LDS,2*N)
              If INFO = 0, the leading 2N-by-2N part of this array
              contains the Hamiltonian or symplectic matrix of the
              problem.

      LDS     INTEGER
              The leading dimension of array S.  LDS >= MAX(1,2*N).

Workspace

      IWORK   INTEGER array, dimension (2*N)

      DWORK   DOUBLE PRECISION array, dimension (LDWORK)
              On exit, if INFO = 0, DWORK(1) returns the optimal value
              of LDWORK; if DICO = 'D', DWORK(2) returns the reciprocal
              condition number of the given matrix  A.

      LDWORK  INTEGER
              The length of the array DWORK.
              LDWORK >= 1          if DICO = 'C';
              LDWORK >= MAX(2,4*N) if DICO = 'D'.
              For optimum performance LDWORK should be larger, if
              DICO = 'D'.

              If LDWORK = -1, then a workspace query is assumed;
              the routine only calculates the optimal size of the
              DWORK array, returns this value as the first entry of
              the DWORK array, and no error message related to LDWORK
              is issued by XERBLA.

Error Indicator

      INFO    INTEGER
              = 0:  successful exit;
              < 0:  if INFO = -i, the i-th argument had an illegal
                    value;
              = i:  if the leading i-by-i (1 <= i <= N) upper triangular
                    submatrix of A is singular in discrete-time case;
              = N+1:  if matrix A is numerically singular in discrete-
                    time case.

Method

      For a continuous-time problem, the 2n-by-2n Hamiltonian matrix (1)
      is constructed.
      For a discrete-time problem, the 2n-by-2n symplectic matrix (2) or
      (3) - the inverse of the matrix in (2) - is constructed.

Numerical Aspects

      The discrete-time case needs the inverse of the matrix A, hence
      the routine should not be used when A is ill-conditioned.
                                3
      The algorithm requires 0(n ) floating point operations in the
      discrete-time case.

Further Comments

      None

Example

Program Text

      None

Program Data

      None

Program Results

      None

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