SG03BZ - SLICOT Library Routine Documentation

## SG03BZ

### Solving (for Cholesky factor) stable generalized continuous- or discrete-time complex Lyapunov equations

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

Purpose

      To compute the Cholesky factor U of the matrix X,

                  H
         X = op(U)  * op(U),

      which is the solution of either the generalized c-stable
      continuous-time Lyapunov equation

              H                    H
         op(A)  * X * op(E) + op(E)  * X * op(A)

                  2        H
         = - SCALE  * op(B)  * op(B),                                (1)

      or the generalized d-stable discrete-time Lyapunov equation

              H                    H
         op(A)  * X * op(A) - op(E)  * X * op(E)

                  2        H
         = - SCALE  * op(B)  * op(B),                                (2)

      without first finding X and without the need to form the matrix
      op(B)**H * op(B).

      op(K) is either K or K**H for K = A, B, E, U. A and E are N-by-N
      matrices, op(B) is an M-by-N matrix. The resulting matrix U is an
      N-by-N upper triangular matrix with non-negative entries on its
      main diagonal. SCALE is an output scale factor set to avoid
      overflow in U.

      In the continuous-time case (1) the pencil A - lambda * E must be
      c-stable (that is, all eigenvalues must have negative real parts).
      In the discrete-time case (2) the pencil A - lambda * E must be
      d-stable (that is, the moduli of all eigenvalues must be smaller
      than one).

Specification

          SUBROUTINE SG03BZ( DICO, FACT, TRANS, N, M, A, LDA, E, LDE, Q,
         $                   LDQ, Z, LDZ, B, LDB, SCALE, ALPHA, BETA, DWORK,
         $                   ZWORK, LZWORK, INFO )
    C     .. Scalar Arguments ..
          DOUBLE PRECISION  SCALE
          INTEGER           INFO, LDA, LDB, LDE, LDQ, LDZ, LZWORK, M, N
          CHARACTER         DICO, FACT, TRANS
    C     .. Array Arguments ..
          COMPLEX*16        A(LDA,*), ALPHA(*), B(LDB,*), BETA(*), E(LDE,*),
         $                  Q(LDQ,*), Z(LDZ,*), ZWORK(*)
          DOUBLE PRECISION  DWORK(*)

Arguments

Mode Parameters

      DICO    CHARACTER*1
              Specifies which type of the equation is considered:
              = 'C':  Continuous-time equation (1);
              = 'D':  Discrete-time equation (2).

      FACT    CHARACTER*1
              Specifies whether the generalized (complex) Schur
              factorization of the pencil A - lambda * E is supplied on
              entry or not:
              = 'N':  Factorization is not supplied;
              = 'F':  Factorization is supplied.

      TRANS   CHARACTER*1
              Specifies whether the conjugate transposed equation is to
              be solved or not:
              = 'N':  op(A) = A,    op(E) = E;
              = 'C':  op(A) = A**H, op(E) = E**H.

Input/Output Parameters

      N       (input) INTEGER
              The order of the matrix A.  N >= 0.

      M       (input) INTEGER
              The number of rows in the matrix op(B).  M >= 0.
              If M = 0, A and E are unchanged on exit, and Q, Z, ALPHA
              and BETA are not set.

      A       (input/output) COMPLEX*16 array, dimension (LDA,N)
              On entry, if FACT = 'F', then the leading N-by-N upper
              triangular part of this array must contain the generalized
              Schur factor A_s of the matrix A (see definition (3) in
              section METHOD). A_s must be an upper triangular matrix.
              The elements below the upper triangular part of the array
              A are used as workspace.
              If FACT = 'N', then the leading N-by-N part of this array
              must contain the matrix A.
              On exit, if FACT = 'N', the leading N-by-N upper
              triangular part of this array contains the generalized
              Schur factor A_s of the matrix A. (A_s is an upper
              triangular matrix.) If FACT = 'F', the leading N-by-N
              upper triangular part of this array is unchanged.

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

      E       (input/output) COMPLEX*16 array, dimension (LDE,N)
              On entry, if FACT = 'F', then the leading N-by-N upper
              triangular part of this array must contain the generalized
              Schur factor E_s of the matrix E (see definition (4) in
              section METHOD). E_s must be an upper triangular matrix.
              The elements below the upper triangular part of the array
              E are used as workspace.
              If FACT = 'N', then the leading N-by-N part of this array
              must contain the coefficient matrix E of the equation.
              On exit, if FACT = 'N', the leading N-by-N upper
              triangular part of this array contains the generalized
              Schur factor E_s of the matrix E. (E_s is an upper
              triangular matrix.) If FACT = 'F', the leading N-by-N
              upper triangular part of this array is unchanged.

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

      Q       (input/output) COMPLEX*16 array, dimension (LDQ,N)
              On entry, if FACT = 'F', then the leading N-by-N part of
              this array must contain the unitary matrix Q from the
              generalized Schur factorization (see definitions (3) and
              (4) in section METHOD), or an identity matrix (if the
              original equation has upper triangular matrices A and E).
              If FACT = 'N', Q need not be set on entry.
              On exit, if FACT = 'N', the leading N-by-N part of this
              array contains the unitary matrix Q from the generalized
              Schur factorization. If FACT = 'F', this array is
              unchanged.

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

      Z       (input/output) COMPLEX*16 array, dimension (LDZ,N)
              On entry, if FACT = 'F', then the leading N-by-N part of
              this array must contain the unitary matrix Z from the
              generalized Schur factorization (see definitions (3) and
              (4) in section METHOD), or an identity matrix (if the
              original equation has upper triangular matrices A and E).
              If FACT = 'N', Z need not be set on entry.
              On exit, if FACT = 'N', the leading N-by-N part of this
              array contains the unitary matrix Z from the generalized
              Schur factorization. If FACT = 'F', this array is
              unchanged.

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

      B       (input/output) COMPLEX*16 array, dimension (LDB,N1)
              On entry, if TRANS = 'C', the leading N-by-M part of this
              array must contain the matrix B and N1 >= MAX(M,N).
              If TRANS = 'N', the leading M-by-N part of this array
              must contain the matrix B and N1 >= N.
              On exit, if INFO = 0, the leading N-by-N part of this
              array contains the Cholesky factor U of the solution
              matrix X of the problem, X = op(U)**H * op(U).
              If M = 0 and N > 0, then U is set to zero.

      LDB     INTEGER
              The leading dimension of the array B.
              If TRANS = 'C',  LDB >= MAX(1,N).
              If TRANS = 'N',  LDB >= MAX(1,M,N).

      SCALE   (output) DOUBLE PRECISION
              The scale factor set to avoid overflow in U.
              0 < SCALE <= 1.

      ALPHA   (output) COMPLEX*16 arrays, dimension (N)
      BETA    If INFO = 0, 5, 6, or 7, then ALPHA(j)/BETA(j),
              j = 1, ... , N, are the eigenvalues of the matrix pencil
              A - lambda * E (the diagonals of the complex Schur form).
              All BETA(j) are non-negative real numbers.
              ALPHA will be always less than and usually comparable with
              norm(A) in magnitude, and BETA always less than and
              usually comparable with norm(B).

Workspace

      DWORK   DOUBLE PRECISION array, dimension (LDWORK), where
              LDWORK = 0,           if MIN(M,N) = 0 or
                                       FACT = 'F' and N <= 1; else,
              LDWORK = N-1,         if FACT = 'F' and DICO = 'C';
              LDWORK = MAX(N-1,10), if FACT = 'F' and DICO = 'D';
              LDWORK = 8*N,         if FACT = 'N'.

      ZWORK   COMPLEX*16 array, dimension (LZWORK)
              On exit, if INFO = 0, ZWORK(1) returns the optimal value
              of LZWORK.
              On exit, if INFO = -21, ZWORK(1) returns the minimum value
              of LZWORK.

      LZWORK  INTEGER
              The dimension of the array ZWORK.
              LZWORK >= MAX(1,3*N-3,2*N).
              For good performance, LZWORK should be larger.

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

Error Indicator

      INFO    INTEGER
              = 0:  successful exit;
              < 0:  if INFO = -i, the i-th argument had an illegal
                    value;
              = 4:  FACT = 'N' and the pencil A - lambda * E cannot be
                    reduced to generalized Schur form: LAPACK routine
                    ZGGES has failed to converge;
              = 5:  DICO = 'C' and the pencil A - lambda * E is not
                    c-stable;
              = 6:  DICO = 'D' and the pencil A - lambda * E is not
                    d-stable;
              = 7:  the LAPACK routine ZSTEIN utilized to factorize M3
                    failed to converge in the discrete-time case (see
                    section METHOD for SLICOT Library routine SG03BS).
                    This error is unlikely to occur.

Method

      An extension [2] of Hammarling's method [1] to generalized
      Lyapunov equations is utilized to solve (1) or (2).

      First the pencil A - lambda * E is reduced to complex generalized
      Schur form A_s - lambda * E_s by means of unitary transformations
      (QZ-algorithm):

         A_s = Q**H * A * Z   (upper triangular),                    (3)

         E_s = Q**H * E * Z   (upper triangular).                    (4)

      If the pencil A - lambda * E has already been factorized prior to
      calling the routine, however, then the factors A_s, E_s, Q and Z
      may be supplied and the initial factorization omitted.

      Depending on the parameters TRANS and M, the N-by-N upper
      triangular matrix B_s is defined as follows. In any case Q_B is
      an M-by-M unitary matrix, which need not be accumulated.

      1. If TRANS = 'N' and M < N, B_s is the upper triangular matrix
         from the QR-factorization

            ( Q_B  O )           ( B * Z )
            (        ) * B_s  =  (       ),
            (  O   I )           (   O   )

         where the O's are zero matrices of proper size and I is the
         identity matrix of order N-M.

      2. If TRANS = 'N' and M >= N, B_s is the upper triangular matrix
         from the (rectangular) QR-factorization

                  ( B_s )
            Q_B * (     )  =  B * Z,
                  (  O  )

         where O is the (M-N)-by-N zero matrix.

      3. If TRANS = 'C' and M < N, B_s is the upper triangular matrix
         from the RQ-factorization

                        ( Q_B  O )
            (B_s  O ) * (        )  =  ( Q**H * B   O ).
                        (  O   I )

      4. If TRANS = 'C' and M >= N, B_s is the upper triangular matrix
         from the (rectangular) RQ-factorization

            ( B_s   O ) * Q_B  =  Q**H * B,

         where O is the N-by-(M-N) zero matrix.

      Assuming SCALE = 1, the transformation of A, E and B described
      above leads to the reduced continuous-time equation

                  H        H
           op(A_s)  op(U_s)  op(U_s) op(E_s)

                  H        H
         + op(E_s)  op(U_s)  op(U_s) op(A_s)

                     H
         =  - op(B_s)  op(B_s)                                       (5)

      or to the reduced discrete-time equation

                  H        H
           op(A_s)  op(U_s)  op(U_s) op(A_s)

                  H        H
         - op(E_s)  op(U_s)  op(U_s) op(E_s)

                     H
         =  - op(B_s)  op(B_s).                                      (6)

      For brevity we restrict ourself to equation (5) and the case
      TRANS = 'N'. The other three cases can be treated in a similar
      fashion.

      We use the following partitioning for the matrices A_s, E_s, B_s,
      and U_s

                  ( A11   A12 )          ( E11   E12 )
            A_s = (           ),   E_s = (           ),
                  (   0   A22 )          (   0   E22 )

                  ( B11   B12 )          ( U11   U12 )
            B_s = (           ),   U_s = (           ).              (7)
                  (   0   B22 )          (   0   U22 )

      The size of the (1,1)-blocks is 1-by-1.

      We compute U11, U12**H, and U22 in three steps.

      Step I:

         From (5) and (7) we get the 1-by-1 equation

                 H      H                   H      H
              A11  * U11  * U11 * E11  + E11  * U11  * U11 * A11

                     H
              = - B11  * B11.

         For brevity, details are omitted here. See [2]. The technique
         for computing U11 is similar to those applied to standard
         Lyapunov equations in Hammarling's algorithm ([1], section 5).

         Furthermore, the auxiliary scalars M1 and M2 defined as follows

            M1 = A11 / E11 ,

            M2 = B11 / E11 / U11 ,

         are computed in a numerically reliable way.

      Step II:

         The generalized Sylvester equation

               H      H      H      H
            A22  * U12  + E22  * U12  * M1  =

                 H           H      H      H      H
            - B12  * M2 - A12  * U11  - E12  * U11  * M1

         is solved for U12**H, as a linear system of order N-1.

      Step III:

         It can be shown that

               H      H                  H      H
            A22  * U22  * U22 * E22 + E22  * U22  * U22 * A22  =

                 H              H
            - B22  * B22 - y * y                                     (8)

         holds, where y is defined as

                   H        H      H      H      H
            y = B12  - ( E12  * U11  + E22  * U12  ) * M2 .

         If B22_tilde is the square triangular matrix arising from the
         (rectangular) QR-factorization

                        ( B22_tilde )     ( B22  )
            Q_B_tilde * (           )  =  (      ),
                        (     O     )     ( y**H )

         where Q_B_tilde is a unitary matrix of order N, then

                 H              H                H
            - B22  * B22 - y * y   =  - B22_tilde  * B22_tilde.

         Replacing the right hand side in (8) by the term
         - B22_tilde**H * B22_tilde leads to a reduced generalized
         Lyapunov equation like (5), but of dimension N-1.

      The recursive application of the steps I to III yields the
      solution U_s of the equation (5).

      It remains to compute the solution matrix U of the original
      problem (1) or (2) from the matrix U_s. To this end we transform
      the solution back (with respect to the transformation that led
      from (1) to (5) (from (2) to (6)) and apply the QR-factorization
      (RQ-factorization). The upper triangular solution matrix U is
      obtained by

         Q_U * U  =  U_s * Q**H     (if TRANS = 'N'),

      or

         U * Q_U  =  Z * U_s        (if TRANS = 'C'),

      where Q_U is an N-by-N unitary matrix. Again, the unitary matrix
      Q_U need not be accumulated.

References

      [1] Hammarling, S.J.
          Numerical solution of the stable, non-negative definite
          Lyapunov equation.
          IMA J. Num. Anal., 2, pp. 303-323, 1982.

      [2] Penzl, T.
          Numerical solution of generalized Lyapunov equations.
          Advances in Comp. Math., vol. 8, pp. 33-48, 1998.

Numerical Aspects

      The number of flops required by the routine is given by the
      following table. Note that we count a single floating point
      arithmetic operation as one flop.

                  |           FACT = 'F'                  FACT = 'N'
         ---------+--------------------------------------------------
          M <= N  |     (13*N**3+6*M*N**2         (211*N**3+6*M*N**2
                  |   +6*M**2*N-2*M**3)/3        +6*M**2*N-2*M**3)/3
                  |
           M > N  | (11*N**3+12*M*N**2)/3     (209*N**3+12*M*N**2)/3

Further Comments

      The Lyapunov equation may be very ill-conditioned. In particular,
      if DICO = 'D' and the pencil A - lambda * E has a pair of almost
      reciprocal eigenvalues, or DICO = 'C' and the pencil has an almost
      degenerate pair of eigenvalues, then the Lyapunov equation will be
      ill-conditioned. Perturbed values were used to solve the equation.
      A condition estimate can be obtained from the routine SG03AD.

Example

Program Text

      None

Program Data

      None

Program Results

      None

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