AB09JV - SLICOT Library Routine Documentation

## AB09JV

### State-space representation of a projection of a left weighted transfer-function matrix

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

Purpose

      To construct a state-space representation (A,BS,CS,DS) of the
      projection of V*G or conj(V)*G containing the poles of G, from the
      state-space representations (A,B,C,D) and (AV-lambda*EV,BV,CV,DV),
      of the transfer-function matrices G and V, respectively.
      G is assumed to be a stable transfer-function matrix and
      the state matrix A must be in a real Schur form.
      When computing the stable projection of V*G, it is assumed
      that G and V have completely distinct poles.
      When computing the stable projection of conj(V)*G, it is assumed
      that G and conj(V) have completely distinct poles.

      Note: For a transfer-function matrix G, conj(G) denotes the
      conjugate of G given by G'(-s) for a continuous-time system or
      G'(1/z) for a discrete-time system.

Specification

          SUBROUTINE AB09JV( JOB, DICO, JOBEV, STBCHK, N, M, P, NV, PV,
         $                   A, LDA, B, LDB, C, LDC, D, LDD, AV, LDAV,
         $                   EV, LDEV, BV, LDBV, CV, LDCV, DV, LDDV, IWORK,
         $                   DWORK, LDWORK, INFO )
    C     .. Scalar Arguments ..
          CHARACTER         DICO, JOB, JOBEV, STBCHK
          INTEGER           INFO, LDA, LDAV, LDB, LDBV, LDC, LDCV,
         $                  LDD, LDDV, LDEV, LDWORK, M, N, NV, P, PV
    C     .. Array Arguments ..
          INTEGER           IWORK(*)
          DOUBLE PRECISION  A(LDA,*), AV(LDAV,*), B(LDB,*), BV(LDBV,*),
         $                  C(LDC,*), CV(LDCV,*), D(LDD,*), DV(LDDV,*),
         $                  DWORK(*), EV(LDEV,*)

Arguments

Mode Parameters

      JOB     CHARACTER*1
              Specifies the projection to be computed as follows:
              = 'V':  compute the projection of V*G containing
                      the poles of G;
              = 'C':  compute the projection of conj(V)*G containing
                      the poles of G.

      DICO    CHARACTER*1
              Specifies the type of the systems as follows:
              = 'C':  G and V are continuous-time systems;
              = 'D':  G and V are discrete-time systems.

      JOBEV   CHARACTER*1
              Specifies whether EV is a general square or an identity
              matrix as follows:
              = 'G':  EV is a general square matrix;
              = 'I':  EV is the identity matrix.

      STBCHK  CHARACTER*1
              Specifies whether stability/antistability of V is to be
              checked as follows:
              = 'C':  check stability if JOB = 'C' or antistability if
                      JOB = 'V';
              = 'N':  do not check stability or antistability.

Input/Output Parameters

      N       (input) INTEGER
              The dimension of the state vector of the system with
              the transfer-function matrix G.  N >= 0.

      M       (input) INTEGER
              The dimension of the input vector of the system with
              the transfer-function matrix G.  M >= 0.

      P       (input) INTEGER
              The dimension of the output vector of the system with the
              transfer-function matrix G, and also the dimension of
              the input vector if JOB = 'V', or of the output vector
              if JOB = 'C', of the system with the transfer-function
              matrix V.  P >= 0.

      NV      (input) INTEGER
              The dimension of the state vector of the system with
              the transfer-function matrix V.  NV >= 0.

      PV      (input) INTEGER
              The dimension of the output vector, if JOB = 'V', or
              of the input vector, if JOB = 'C', of the system with
              the transfer-function matrix V.  PV >= 0.

      A       (input) DOUBLE PRECISION array, dimension (LDA,N)
              The leading N-by-N part of this array must contain the
              state matrix A of the system with the transfer-function
              matrix G in a real Schur form.

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

      B       (input) DOUBLE PRECISION array, dimension (LDB,M)
              The leading N-by-M part of this array must contain
              the input/state matrix B of the system with the
              transfer-function matrix G. The matrix BS is equal to B.

      LDB     INTEGER
              The leading dimension of the array B.  LDB >= MAX(1,N).

      C       (input/output) DOUBLE PRECISION array, dimension (LDC,N)
              On entry, the leading P-by-N part of this array must
              contain the output matrix C of the system with the
              transfer-function matrix G.
              On exit, if INFO = 0, the leading PV-by-N part of this
              array contains the output matrix CS of the projection of
              V*G, if JOB = 'V', or of conj(V)*G, if JOB = 'C'.

      LDC     INTEGER
              The leading dimension of the array C.  LDC >= MAX(1,P,PV).

      D       (input/output) DOUBLE PRECISION array, dimension (LDD,M)
              On entry, the leading P-by-M part of this array must
              contain the feedthrough matrix D of the system with the
              transfer-function matrix G.
              On exit, if INFO = 0, the leading PV-by-M part of
              this array contains the feedthrough matrix DS of the
              projection of V*G, if JOB = 'V', or of conj(V)*G,
              if JOB = 'C'.

      LDD     INTEGER
              The leading dimension of the array D.  LDD >= MAX(1,P,PV).

      AV      (input/output) DOUBLE PRECISION array, dimension (LDAV,NV)
              On entry, the leading NV-by-NV part of this array must
              contain the state matrix AV of the system with the
              transfer-function matrix V.
              On exit, if INFO = 0, the leading NV-by-NV part of this
              array contains a condensed matrix as follows:
              if JOBEV = 'I', it contains the real Schur form of AV;
              if JOBEV = 'G' and JOB = 'V', it contains a quasi-upper
              triangular matrix representing the real Schur matrix
              in the real generalized Schur form of the pair (AV,EV);
              if JOBEV = 'G', JOB = 'C' and DICO = 'C', it contains a
              quasi-upper triangular matrix corresponding to the
              generalized real Schur form of the pair (AV',EV');
              if JOBEV = 'G', JOB = 'C' and DICO = 'D', it contains an
              upper triangular matrix corresponding to the generalized
              real Schur form of the pair (EV',AV').

      LDAV    INTEGER
              The leading dimension of the array AV.  LDAV >= MAX(1,NV).

      EV      (input/output) DOUBLE PRECISION array, dimension (LDEV,NV)
              On entry, if JOBEV = 'G', the leading NV-by-NV part of
              this array must contain the descriptor matrix EV of the
              system with the transfer-function matrix V.
              If JOBEV = 'I', EV is assumed to be an identity matrix
              and is not referenced.
              On exit, if INFO = 0 and JOBEV = 'G', the leading NV-by-NV
              part of this array contains a condensed matrix as follows:
              if JOB = 'V', it contains an upper triangular matrix
              corresponding to the real generalized Schur form of the
              pair (AV,EV);
              if JOB = 'C' and DICO = 'C', it contains an upper
              triangular matrix corresponding to the generalized real
              Schur form of the pair (AV',EV');
              if JOB = 'C' and DICO = 'D', it contains a quasi-upper
              triangular matrix corresponding to the generalized
              real Schur form of the pair (EV',AV').

      LDEV    INTEGER
              The leading dimension of the array EV.
              LDEV >= MAX(1,NV), if JOBEV = 'G';
              LDEV >= 1,         if JOBEV = 'I'.

      BV      (input/output) DOUBLE PRECISION array,
              dimension (LDBV,MBV), where MBV = P, if JOB = 'V', and
              MBV = PV, if JOB = 'C'.
              On entry, the leading NV-by-MBV part of this array must
              contain the input matrix BV of the system with the
              transfer-function matrix V.
              On exit, if INFO = 0, the leading NV-by-MBV part of this
              array contains Q'*BV, where Q is the orthogonal matrix
              that reduces AV to the real Schur form or the left
              orthogonal matrix used to reduce the pair (AV,EV),
              (AV',EV') or (EV',AV') to the generalized real Schur form.

      LDBV    INTEGER
              The leading dimension of the array BV.  LDBV >= MAX(1,NV).

      CV      (input/output) DOUBLE PRECISION array, dimension (LDCV,NV)
              On entry, the leading PCV-by-NV part of this array must
              contain the output matrix CV of the system with the
              transfer-function matrix V, where PCV = PV, if JOB = 'V',
              or PCV = P, if JOB = 'C'.
              On exit, if INFO = 0, the leading PCV-by-NV part of this
              array contains CV*Q, where Q is the orthogonal matrix that
              reduces AV to the real Schur form, or CV*Z, where Z is the
              right orthogonal matrix used to reduce the pair (AV,EV),
              (AV',EV') or (EV',AV') to the generalized real Schur form.

      LDCV    INTEGER
              The leading dimension of the array CV.
              LDCV >= MAX(1,PV) if JOB = 'V';
              LDCV >= MAX(1,P)  if JOB = 'C'.

      DV      (input) DOUBLE PRECISION array,
              dimension (LDDV,MBV), where MBV = P, if JOB = 'V', and
              MBV = PV, if JOB = 'C'.
              The leading PCV-by-MBV part of this array must contain
              the feedthrough matrix DV of the system with the
              transfer-function matrix V, where PCV = PV, if JOB = 'V',
              or PCV = P, if JOB = 'C'.

      LDDV    INTEGER
              The leading dimension of the array DV.
              LDDV >= MAX(1,PV) if JOB = 'V';
              LDDV >= MAX(1,P)  if JOB = 'C'.

Workspace

      IWORK   INTEGER array, dimension (LIWORK)
              LIWORK =   0,    if JOBEV = 'I';
              LIWORK = NV+N+6, if JOBEV = 'G'.

      DWORK   DOUBLE PRECISION array, dimension (LDWORK)
              On exit, if INFO = 0, DWORK(1) returns the optimal value
              of LDWORK.

      LDWORK  INTEGER
              The length of the array DWORK.
              LDWORK >= LW1, if JOBEV = 'I',
              LDWORK >= LW2, if JOBEV = 'G', where
                LW1 = MAX( 1, NV*(NV+5), NV*N + MAX( a, PV*N, PV*M ) )
                      a = 0,    if DICO = 'C' or  JOB = 'V',
                      a = 2*NV, if DICO = 'D' and JOB = 'C';
                LW2 = MAX( 2*NV*NV + MAX( 11*NV+16, P*NV, PV*NV ),
                           NV*N + MAX( NV*N+N*N, PV*N, PV*M ) ).
              For good performance, LDWORK should be larger.

Error Indicator

      INFO    INTEGER
              =  0:  successful exit;
              <  0:  if INFO = -i, the i-th argument had an illegal
                     value;
              =  1:  the reduction of the pair (AV,EV) to the real
                     generalized Schur form failed (JOBEV = 'G'),
                     or the reduction of the matrix AV to the real
                     Schur form failed (JOBEV = 'I);
              =  2:  the solution of the Sylvester equation failed
                     because the matrix A and the pencil AV-lambda*EV
                     have common eigenvalues (if JOB = 'V'), or the
                     pencil -AV-lambda*EV and A have common eigenvalues
                     (if JOB = 'C' and DICO = 'C'), or the pencil
                     AV-lambda*EV has an eigenvalue which is the
                     reciprocal of one of eigenvalues of A
                     (if JOB = 'C' and DICO = 'D');
              =  3:  the solution of the Sylvester equation failed
                     because the matrices A and AV have common
                     eigenvalues (if JOB = 'V'), or the matrices A
                     and -AV have common eigenvalues (if JOB = 'C' and
                     DICO = 'C'), or the matrix A has an eigenvalue
                     which is the reciprocal of one of eigenvalues of AV
                     (if JOB = 'C' and DICO = 'D');
              =  4:  JOB = 'V' and the pair (AV,EV) has not completely
                     unstable generalized eigenvalues, or JOB = 'C' and
                     the pair (AV,EV) has not completely stable
                     generalized eigenvalues.

Method

      If JOB = 'V', the matrices of the stable projection of V*G are
      computed as

        BS = B,  CS = CV*X + DV*C,  DS = DV*D,

      where X satisfies the generalized Sylvester equation

        AV*X - EV*X*A + BV*C = 0.

      If JOB = 'C', the matrices of the stable projection of conj(V)*G
      are computed using the following formulas:

      - for a continuous-time system, the matrices BS, CS and DS of
        the stable projection are computed as

          BS = B,  CS = BV'*X + DV'*C,  DS = DV'*D,

        where X satisfies the generalized Sylvester equation

          AV'*X + EV'*X*A + CV'*C = 0.

      - for a discrete-time system, the matrices BS, CS and DS of
        the stable projection are computed as

          BS = B,  CS = BV'*X*A + DV'*C,  DS = DV'*D + BV'*X*B,

        where X satisfies the generalized Sylvester equation

          EV'*X - AV'*X*A = CV'*C.

References

      [1] Varga, A.
          Efficient and numerically reliable implementation of the
          frequency-weighted Hankel-norm approximation model reduction
          approach.
          Proc. 2001 ECC, Porto, Portugal, 2001.

      [2] Zhou, K.
          Frequency-weighted H-infinity norm and optimal Hankel norm
          model reduction.
          IEEE Trans. Autom. Control, vol. 40, pp. 1687-1699, 1995.

Numerical Aspects

      The implemented methods rely on numerically stable algorithms.

Further Comments

      None

Example

Program Text

      None

Program Data

      None

Program Results

      None

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