DGHUYR

Reducing a special real block (anti-)diagonal skew-Hamiltonian/Hamiltonian pencil in factored form
to generalized Schur form (unfactored version)

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

Purpose

     To compute the transformed matrices A and B, using orthogonal
     matrices Q1 and Q2 for a real N-by-N regular pencil

                   ( A11   0  )     (  0   B12 )
       aA - bB = a (          ) - b (          ),                   (1)
                   (  0   A22 )     ( B21   0  )

     where A11, A22 and B12 are upper triangular, B21 is upper
     quasi-triangular and the generalized matrix product
        -1        -1
     A11   B12 A22   B21 is in periodic Schur form, such that the
     matrix Q2' A Q1 is upper triangular, Q2' B Q1 is upper
     quasi-triangular and the transformed pencil
     a(Q2' A Q1) - b(Q2' B Q1) is in generalized Schur form. The
     notation M' denotes the transpose of the matrix M.
Specification
      SUBROUTINE DGHUYR( COMPQ1, COMPQ2, N, A, LDA, B, LDB, Q1, LDQ1,
     $                   Q2, LDQ2, IWORK, LIWORK, DWORK, LDWORK, BWORK,
     $                   INFO )
C
C     .. Scalar Arguments ..
      CHARACTER          COMPQ1, COMPQ2
      INTEGER            INFO, LDA, LDB, LDQ1, LDQ2, LDWORK, LIWORK, N
C
C     .. Array Arguments ..
      LOGICAL            BWORK( * )
      INTEGER            IWORK( * )
      DOUBLE PRECISION   A( LDA, * ), B( LDB, * ), DWORK( * ),
     $                   Q1( LDQ1, * ), Q2( LDQ2, * )
Arguments

Mode Parameters

     COMPQ1  CHARACTER*1
             Specifies whether to compute the orthogonal transformation
             matrix Q1, as follows:
             = 'N':  Q1 is not computed;
             = 'I':  the array Q1 is initialized internally to the unit
                     matrix, and the orthogonal matrix Q1 is returned;
             = 'U':  the array Q1 contains an orthogonal matrix Q01 on
                     entry, and the matrix Q01*Q1 is returned, where Q1
                     is the product of the orthogonal transformations
                     that are applied on the right to the pencil
                     aA - bB in (1).

     COMPQ2  CHARACTER*1
             Specifies whether to compute the orthogonal transformation
             matrix Q2, as follows:
             = 'N':  Q2 is not computed;
             = 'I':  the array Q2 is initialized internally to the unit
                     matrix, and the orthogonal matrix Q2 is returned;
             = 'U':  the array Q2 contains an orthogonal matrix Q02 on
                     entry, and the matrix Q02*Q2 is returned, where Q2
                     is the product of the orthogonal transformations
                     that are applied on the left to the pencil aA - bB
                     in (1).             
Input/Output Parameters
     N       (input) INTEGER
             Order of the pencil aA - bB, N >= 0, even.

     A       (input/output) DOUBLE PRECISION array, dimension (LDA, N)
             On entry, the leading N-by-N block diagonal part of this
             array must contain the matrix A in (1). The off-diagonal
             blocks need not be set to zero.
             On exit, the leading N-by-N part of this array contains
             the transformed upper triangular matrix.

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

     B       (input/output) DOUBLE PRECISION array, dimension (LDB, N)
             On entry, the leading N-by-N block anti-diagonal part of
             this array must contain the matrix B in (1). The diagonal
             blocks need not be set to zero.
             On exit, the leading N-by-N part of this array contains
             the transformed upper quasi-triangular matrix.

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

     Q1      (input/output) DOUBLE PRECISION array, dimension (LDQ1, N)
             On entry, if COMPQ1 = 'U', then the leading N-by-N part of
             this array must contain a given matrix Q01, and on exit,
             the leading N-by-N part of this array contains the product
             of the input matrix Q01 and the transformation matrix Q1
             used to transform the matrices A and B.
             On exit, if COMPQ1 = 'I', then the leading N-by-N part of
             this array contains the orthogonal transformation matrix
             Q1.
             If COMPQ1 = 'N' this array is not referenced.

     LDQ1    INTEGER
             The leading dimension of the array Q1.
             LDQ1 >= 1,         if COMPQ1 = 'N';
             LDQ1 >= MAX(1, N), if COMPQ1 = 'I' or COMPQ1 = 'U'.

     Q2      (input/output) DOUBLE PRECISION array, dimension (LDQ2, N)
             On entry, if COMPQ2 = 'U', then the leading N-by-N part of
             this array must contain a given matrix Q02, and on exit,
             the leading N-by-N part of this array contains the product
             of the input matrix Q02 and the transformation matrix Q2
             used to transform the matrices A and B.
             On exit, if COMPQ2 = 'I', then the leading N-by-N part of
             this array contains the orthogonal transformation matrix
             Q2.
             If COMPQ2 = 'N' this array is not referenced.

     LDQ2    INTEGER
             The leading dimension of the array Q2.
             LDQ2 >= 1,         if COMPQ2 = 'N';
             LDQ2 >= MAX(1, N), if COMPQ2 = 'I' or COMPQ2 = 'U'.
Workspace
     IWORK   INTEGER array, dimension (LIWORK)

     LIWORK  INTEGER
             The dimension of the array IWORK.
             LIWORK >= MAX( N/2+1, 32 ).

     DWORK   DOUBLE PRECISION array, dimension (LDWORK)
             On exit, if INFO = 0, DWORK(1) returns the optimal LDWORK.
             On exit, if INFO = -16, DWORK(1) returns the minimum value
             of LDWORK.

     LDWORK  INTEGER
             The dimension of the array DWORK.
             LDWORK >= 2*N*N + MAX( N/2 + 168, 272 ).
             For good performance LDWORK should be generally larger.

             If LDWORK = -1  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 is issued by XERBLA. 

     BWORK   LOGICAL array, dimension (N/2)
Error Indicator
     INFO    INTEGER
             = 0: succesful exit;
             < 0: if INFO = -i, the i-th argument had an illegal value;
             = 1: the periodic QZ algorithm failed to reorder the
                  eigenvalues (the problem is very ill-conditioned) in
                  the SLICOT Library routine MB03KD;
             = 2: the standard QZ algorithm failed in the LAPACK
                  routine DGGEV, called by the routine DGHUEX;
             = 3: the standard QZ algorithm failed in the LAPACK
                  routines DGGES or DHGEQZ, called by the routines
                  DGHUEX or DGHUET;
             = 4: the standard QZ algorithm failed to reorder the
                  eigenvalues in the LAPACK routine DTGSEN, called by
                  the routine DGHUEX.
Method
     First, the periodic QZ algorithm (see also [2] and [3]) is applied
                                     -1        -1
     to the formal matrix product A11   B12 A22   B21 to reorder the
     eigenvalues, i.e., orthogonal matrices V1, V2, V3 and V4 are
     computed such that V2' A11 V1, V2' B12 V3, V4' A22 V3 and
     V4' B21 V1 keep the triangular form, but they can be partitioned
     into 2-by-2 block forms and the last diagonal blocks correspond to
     all nonpositive real eigenvalues of the formal product, and the
     first diagonal blocks correspond to the remaining eigenvalues.

     Second, Q1 = diag(V1, V3), Q2 = diag(V2, V4) and

                      ( AA11 AA12   0    0  )
                      (                     )
                      (   0  AA22   0    0  )
     A := Q2' A Q1 =: (                     ),
                      (   0    0  AA33 AA34 )
                      (                     )
                      (   0    0    0  AA44 )

                      (   0    0  BB13 BB14 )
                      (                     )
                      (   0    0    0  BB24 )
     B := Q2' B Q1 =: (                     ),
                      ( BB31 BB32   0    0  )
                      (                     )
                      (   0  BB42   0    0  )

                            -1          -1
     are set, such that AA22   BB24 AA44   BB42 has only nonpositive
     real eigenvalues.

     Third, the permutation matrix

         (  I  0  0  0  )
         (              )
         (  0  0  I  0  )
     P = (              ),
         (  0  I  0  0  )
         (              )
         (  0  0  0  I  )

     where I denotes the identity matrix of appropriate size, is used
     to transform aA - bB to block upper triangular form

                   ( AA11   0  | AA12   0  )
                   (           |           )
                   (   0  AA33 |   0  AA34 )   ( AA1  *  )
     A := P' A P = (-----------+-----------) = (         ),
                   (   0    0  | AA22   0  )   (  0  AA2 )
                   (           |           )
                   (   0    0  |   0  AA44 )

                   (   0  BB13 |   0  BB14 )
                   (           |           )
                   ( BB31   0  | BB32   0  )   ( BB1  *  )
     B := P' B P = (-----------+-----------) = (         ).
                   (   0    0  |   0  BB24 )   (  0  BB2 )
                   (           |           )
                   (   0    0  | BB42   0  )

     Then, further orthogonal transformations that are provided by
     DGHUET and DGHUEX are used to triangularize the subpencil
     aAA1 - bBB1.

     Finally, the subpencil aAA2 - bBB2 is triangularized by applying a
     special permutation matrix.

     See also page 31 in [1] for more details.
References
     [1] Benner, P., Byers, R., Losse, P., Mehrmann, V. and Xu, H.
         Numerical Solution of Real Skew-Hamiltonian/Hamiltonian
         Eigenproblems.
         Tech. Rep., Technical University Chemnitz, Germany,
         Nov. 2007.

     [2] Bojanczyk, A., Golub, G. H. and Van Dooren, P.
         The periodic Schur decomposition: algorithms and applications.
         In F.T. Luk (editor), Advanced Signal Processing Algorithms,
         Architectures, and Implementations III, Proc. SPIE Conference,
         vol. 1770, pp. 31-42, 1992.

     [3] Hench, J. J. and Laub, A. J.
         Numerical Solution of the discrete-time periodic Riccati
         equation. IEEE Trans. Automat. Control, 39, 1197-1210, 1994.
Numerical Aspects
     
                                                               3
     The algorithm is numerically backward stable and needs O(N ) real
     floating point operations.
Further Comments
   
     None.
Example

Program Text

     None.
Program Data
     None.   
Program Results
     None.

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