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SUBROUTINE AB09IY( DICO, JOBC, JOBO, WEIGHT, N, M, P, NV, PV,
$ NW, MW, ALPHAC, ALPHAO, A, LDA, B, LDB, C, LDC,
$ AV, LDAV, BV, LDBV, CV, LDCV, DV, LDDV,
$ AW, LDAW, BW, LDBW, CW, LDCW, DW, LDDW,
$ SCALEC, SCALEO, S, LDS, R, LDR,
$ DWORK, LDWORK, INFO )
C
C PURPOSE
C
C To compute for given state-space representations
C (A,B,C,0), (AV,BV,CV,DV), and (AW,BW,CW,DW) of the
C transfer-function matrices G, V and W, respectively,
C the Cholesky factors of the frequency-weighted
C controllability and observability Grammians corresponding
C to a frequency-weighted model reduction problem.
C G, V and W must be stable transfer-function matrices with
C the state matrices A, AV, and AW in real Schur form.
C It is assumed that the state space realizations (AV,BV,CV,DV)
C and (AW,BW,CW,DW) are minimal. In case of possible pole-zero
C cancellations in forming V*G and/or G*W, the parameters for the
C choice of frequency-weighted Grammians ALPHAO and/or ALPHAC,
C respectively, must be different from 1.
C
C ARGUMENTS
C
C Mode Parameters
C
C DICO CHARACTER*1
C Specifies the type of the systems as follows:
C = 'C': G, V and W are continuous-time systems;
C = 'D': G, V and W are discrete-time systems.
C
C JOBC CHARACTER*1
C Specifies the choice of frequency-weighted controllability
C Grammian as follows:
C = 'S': choice corresponding to a combination method [4]
C of the approaches of Enns [1] and Lin-Chiu [2,3];
C = 'E': choice corresponding to the stability enhanced
C modified combination method of [4].
C
C JOBO CHARACTER*1
C Specifies the choice of frequency-weighted observability
C Grammian as follows:
C = 'S': choice corresponding to a combination method [4]
C of the approaches of Enns [1] and Lin-Chiu [2,3];
C = 'E': choice corresponding to the stability enhanced
C modified combination method of [4].
C
C WEIGHT CHARACTER*1
C Specifies the type of frequency weighting, as follows:
C = 'N': no weightings are used (V = I, W = I);
C = 'L': only left weighting V is used (W = I);
C = 'R': only right weighting W is used (V = I);
C = 'B': both left and right weightings V and W are used.
C
C Input/Output Parameters
C
C N (input) INTEGER
C The order of the state-space representation of G, i.e.,
C the order of the matrix A. N >= 0.
C
C M (input) INTEGER
C The number of columns of the matrix B and
C the number of rows of the matrices CW and DW. M >= 0.
C M represents the dimension of the input vector of the
C system with the transfer-function matrix G and
C also the dimension of the output vector of the system
C with the transfer-function matrix W.
C
C P (input) INTEGER
C The number of rows of the matrix C and the
C number of columns of the matrices BV and DV. P >= 0.
C P represents the dimension of the output vector of the
C system with the transfer-function matrix G and
C also the dimension of the input vector of the system
C with the transfer-function matrix V.
C
C NV (input) INTEGER
C The order of the matrix AV. Also the number of rows of
C the matrix BV and the number of columns of the matrix CV.
C NV represents the dimension of the state vector of the
C system with the transfer-function matrix V. NV >= 0.
C
C PV (input) INTEGER
C The number of rows of the matrices CV and DV. PV >= 0.
C PV represents the dimension of the output vector of the
C system with the transfer-function matrix V.
C
C NW (input) INTEGER
C The order of the matrix AW. Also the number of rows of
C the matrix BW and the number of columns of the matrix CW.
C NW represents the dimension of the state vector of the
C system with the transfer-function matrix W. NW >= 0.
C
C MW (input) INTEGER
C The number of columns of the matrices BW and DW. MW >= 0.
C MW represents the dimension of the input vector of the
C system with the transfer-function matrix W.
C
C ALPHAC (input) DOUBLE PRECISION
C Combination method parameter for defining the
C frequency-weighted controllability Grammian (see METHOD);
C ABS(ALPHAC) <= 1.
C
C ALPHAO (input) DOUBLE PRECISION
C Combination method parameter for defining the
C frequency-weighted observability Grammian (see METHOD);
C ABS(ALPHAO) <= 1.
C
C A (input) DOUBLE PRECISION array, dimension (LDA,N)
C The leading N-by-N part of this array must
C contain the state matrix A (of the system with the
C transfer-function matrix G) in a real Schur form.
C
C LDA INTEGER
C The leading dimension of array A. LDA >= MAX(1,N).
C
C B (input) DOUBLE PRECISION array, dimension (LDB,M)
C The leading N-by-M part of this array must contain the
C input/state matrix B.
C
C LDB INTEGER
C The leading dimension of array B. LDB >= MAX(1,N).
C
C C (input) DOUBLE PRECISION array, dimension (LDC,N)
C The leading P-by-N part of this array must contain the
C state/output matrix C.
C
C LDC INTEGER
C The leading dimension of array C. LDC >= MAX(1,P).
C
C AV (input) DOUBLE PRECISION array, dimension (LDAV,NV)
C If WEIGHT = 'L' or 'B', the leading NV-by-NV part of this
C array must contain the state matrix AV (of the system with
C the transfer-function matrix V) in a real Schur form.
C AV is not referenced if WEIGHT = 'R' or 'N'.
C
C LDAV INTEGER
C The leading dimension of array AV.
C LDAV >= MAX(1,NV), if WEIGHT = 'L' or 'B';
C LDAV >= 1, if WEIGHT = 'R' or 'N'.
C
C BV (input) DOUBLE PRECISION array, dimension (LDBV,P)
C If WEIGHT = 'L' or 'B', the leading NV-by-P part of this
C array must contain the input matrix BV of the system with
C the transfer-function matrix V.
C BV is not referenced if WEIGHT = 'R' or 'N'.
C
C LDBV INTEGER
C The leading dimension of array BV.
C LDBV >= MAX(1,NV), if WEIGHT = 'L' or 'B';
C LDBV >= 1, if WEIGHT = 'R' or 'N'.
C
C CV (input) DOUBLE PRECISION array, dimension (LDCV,NV)
C If WEIGHT = 'L' or 'B', the leading PV-by-NV part of this
C array must contain the output matrix CV of the system with
C the transfer-function matrix V.
C CV is not referenced if WEIGHT = 'R' or 'N'.
C
C LDCV INTEGER
C The leading dimension of array CV.
C LDCV >= MAX(1,PV), if WEIGHT = 'L' or 'B';
C LDCV >= 1, if WEIGHT = 'R' or 'N'.
C
C DV (input) DOUBLE PRECISION array, dimension (LDDV,P)
C If WEIGHT = 'L' or 'B', the leading PV-by-P part of this
C array must contain the feedthrough matrix DV of the system
C with the transfer-function matrix V.
C DV is not referenced if WEIGHT = 'R' or 'N'.
C
C LDDV INTEGER
C The leading dimension of array DV.
C LDDV >= MAX(1,PV), if WEIGHT = 'L' or 'B';
C LDDV >= 1, if WEIGHT = 'R' or 'N'.
C
C AW (input) DOUBLE PRECISION array, dimension (LDAW,NW)
C If WEIGHT = 'R' or 'B', the leading NW-by-NW part of this
C array must contain the state matrix AW (of the system with
C the transfer-function matrix W) in a real Schur form.
C AW is not referenced if WEIGHT = 'L' or 'N'.
C
C LDAW INTEGER
C The leading dimension of array AW.
C LDAW >= MAX(1,NW), if WEIGHT = 'R' or 'B';
C LDAW >= 1, if WEIGHT = 'L' or 'N'.
C
C BW (input) DOUBLE PRECISION array, dimension (LDBW,MW)
C If WEIGHT = 'R' or 'B', the leading NW-by-MW part of this
C array must contain the input matrix BW of the system with
C the transfer-function matrix W.
C BW is not referenced if WEIGHT = 'L' or 'N'.
C
C LDBW INTEGER
C The leading dimension of array BW.
C LDBW >= MAX(1,NW), if WEIGHT = 'R' or 'B';
C LDBW >= 1, if WEIGHT = 'L' or 'N'.
C
C CW (input) DOUBLE PRECISION array, dimension (LDCW,NW)
C If WEIGHT = 'R' or 'B', the leading M-by-NW part of this
C array must contain the output matrix CW of the system with
C the transfer-function matrix W.
C CW is not referenced if WEIGHT = 'L' or 'N'.
C
C LDCW INTEGER
C The leading dimension of array CW.
C LDCW >= MAX(1,M), if WEIGHT = 'R' or 'B';
C LDCW >= 1, if WEIGHT = 'L' or 'N'.
C
C DW (input) DOUBLE PRECISION array, dimension (LDDW,MW)
C If WEIGHT = 'R' or 'B', the leading M-by-MW part of this
C array must contain the feedthrough matrix DW of the system
C with the transfer-function matrix W.
C DW is not referenced if WEIGHT = 'L' or 'N'.
C
C LDDW INTEGER
C The leading dimension of array DW.
C LDDW >= MAX(1,M), if WEIGHT = 'R' or 'B';
C LDDW >= 1, if WEIGHT = 'L' or 'N'.
C
C SCALEC (output) DOUBLE PRECISION
C Scaling factor for the controllability Grammian in (1)
C or (3). See METHOD.
C
C SCALEO (output) DOUBLE PRECISION
C Scaling factor for the observability Grammian in (2)
C or (4). See METHOD.
C
C S (output) DOUBLE PRECISION array, dimension (LDS,N)
C The leading N-by-N upper triangular part of this array
C contains the Cholesky factor S of the frequency-weighted
C cotrollability Grammian P = S*S'. See METHOD.
C
C LDS INTEGER
C The leading dimension of array S. LDS >= MAX(1,N).
C
C R (output) DOUBLE PRECISION array, dimension (LDR,N)
C The leading N-by-N upper triangular part of this array
C contains the Cholesky factor R of the frequency-weighted
C observability Grammian Q = R'*R. See METHOD.
C
C LDR INTEGER
C The leading dimension of array R. LDR >= MAX(1,N).
C
C Workspace
C
C DWORK DOUBLE PRECISION array, dimension (LDWORK)
C On exit, if INFO = 0, DWORK(1) returns the optimal value
C of LDWORK.
C
C LDWORK INTEGER
C The length of the array DWORK.
C LDWORK >= MAX( 1, LLEFT, LRIGHT ),
C where
C LLEFT = (N+NV)*(N+NV+MAX(N+NV,PV)+5)
C if WEIGHT = 'L' or 'B' and PV > 0;
C LLEFT = N*(P+5) if WEIGHT = 'R' or 'N' or PV = 0;
C LRIGHT = (N+NW)*(N+NW+MAX(N+NW,MW)+5)
C if WEIGHT = 'R' or 'B' and MW > 0;
C LRIGHT = N*(M+5) if WEIGHT = 'L' or 'N' or MW = 0.
C For optimum performance LDWORK should be larger.
C
C Error Indicator
C
C INFO INTEGER
C = 0: successful exit;
C < 0: if INFO = -i, the i-th argument had an illegal
C value;
C = 1: if the state matrices A and/or AV are not stable or
C not in a real Schur form;
C = 2: if the state matrices A and/or AW are not stable or
C not in a real Schur form;
C = 3: eigenvalues computation failure.
C
C METHOD
C
C Let Pi = Si*Si' and Qo = Ro'*Ro be the Cholesky factored
C controllability and observability Grammians satisfying
C in the continuous-time case
C
C Ai*Pi + Pi*Ai' + scalec^2*Bi*Bi' = 0, (1)
C
C Ao'*Qo + Qo*Ao + scaleo^2*Co'*Co = 0, (2)
C
C and in the discrete-time case
C
C Ai*Pi*Ai' - Pi + scalec^2*Bi*Bi' = 0, (3)
C
C Ao'*Qo*Ao - Qo + scaleo^2*Co'*Co = 0, (4)
C
C where
C
C Ai = ( A B*Cw ) , Bi = ( B*Dw ) ,
C ( 0 Aw ) ( Bw )
C
C Ao = ( A 0 ) , Co = ( Dv*C Cv ) .
C ( Bv*C Av )
C
C Consider the partitioned Grammians
C
C Pi = ( P11 P12 ) and Qo = ( Q11 Q12 ) ,
C ( P12' P22 ) ( Q12' Q22 )
C
C where P11 and Q11 are the leading N-by-N parts of Pi and Qo,
C respectively, and let P0 and Q0 be non-negative definite matrices
C defined in the combination method [4]
C -1
C P0 = P11 - ALPHAC**2*P12*P22 *P21 ,
C -1
C Q0 = Q11 - ALPHAO**2*Q12*Q22 *Q21.
C
C The frequency-weighted controllability and observability
C Grammians, P and Q, respectively, are defined as follows:
C P = P0 if JOBC = 'S' (standard combination method [4]);
C P = P1 >= P0 if JOBC = 'E', where P1 is the controllability
C Grammian defined to enforce stability for a modified combination
C method of [4];
C Q = Q0 if JOBO = 'S' (standard combination method [4]);
C Q = Q1 >= Q0 if JOBO = 'E', where Q1 is the observability
C Grammian defined to enforce stability for a modified combination
C method of [4].
C
C If JOBC = JOBO = 'S' and ALPHAC = ALPHAO = 0, the choice of
C Grammians corresponds to the method of Enns [1], while if
C ALPHAC = ALPHAO = 1, the choice of Grammians corresponds to the
C method of Lin and Chiu [2,3].
C
C The routine computes directly the Cholesky factors S and R
C such that P = S*S' and Q = R'*R according to formulas
C developed in [4]. No matrix inversions are involved.
C
C REFERENCES
C
C [1] Enns, D.
C Model reduction with balanced realizations: An error bound
C and a frequency weighted generalization.
C Proc. CDC, Las Vegas, pp. 127-132, 1984.
C
C [2] Lin, C.-A. and Chiu, T.-Y.
C Model reduction via frequency-weighted balanced realization.
C Control Theory and Advanced Technology, vol. 8,
C pp. 341-351, 1992.
C
C [3] Sreeram, V., Anderson, B.D.O and Madievski, A.G.
C New results on frequency weighted balanced reduction
C technique.
C Proc. ACC, Seattle, Washington, pp. 4004-4009, 1995.
C
C [4] Varga, A. and Anderson, B.D.O.
C Square-root balancing-free methods for the frequency-weighted
C balancing related model reduction.
C (report in preparation)
C
C CONTRIBUTORS
C
C A. Varga, German Aerospace Center, Oberpfaffenhofen, August 2000.
C D. Sima, University of Bucharest, August 2000.
C V. Sima, Research Institute for Informatics, Bucharest, Aug. 2000.
C
C REVISIONS
C
C A. Varga, Australian National University, Canberra, November 2000.
C V. Sima, Research Institute for Informatics, Bucharest, Dec. 2000.
C A. Varga, German Aerospace Center, Oberpfaffenhofen, August 2001.
C
C KEYWORDS
C
C Frequency weighting, model reduction, multivariable system,
C state-space model, state-space representation.
C
C ******************************************************************
C
C .. Parameters ..
DOUBLE PRECISION ZERO, ONE
PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 )
C .. Scalar Arguments ..
CHARACTER DICO, JOBC, JOBO, WEIGHT
INTEGER INFO, LDA, LDAV, LDAW, LDB, LDBV, LDBW,
$ LDC, LDCV, LDCW, LDDV, LDDW, LDR, LDS, LDWORK,
$ M, MW, N, NV, NW, P, PV
DOUBLE PRECISION ALPHAC, ALPHAO, SCALEC, SCALEO
C .. Array Arguments ..
DOUBLE PRECISION A(LDA,*), AV(LDAV,*), AW(LDAW,*),
$ B(LDB,*), BV(LDBV,*), BW(LDBW,*),
$ C(LDC,*), CV(LDCV,*), CW(LDCW,*),
$ DV(LDDV,*), DW(LDDW,*),
$ DWORK(*), R(LDR,*), S(LDS,*)
C .. Local Scalars ..
LOGICAL DISCR, FRWGHT, LEFTW, RIGHTW
INTEGER I, IERR, J, KAW, KTAU, KU, KW, LDU, LW, MBBAR,
$ NNV, NNW, PCBAR
DOUBLE PRECISION T, TOL, WORK
C .. Local Arrays ..
DOUBLE PRECISION DUM(1)
C .. External Functions ..
LOGICAL LSAME
DOUBLE PRECISION DLAMCH
EXTERNAL DLAMCH, LSAME
C .. External Subroutines ..
EXTERNAL DCOPY, DGEMM, DLACPY, DLASET, DSCAL, DSYEV,
$ MB01WD, MB04ND, MB04OD, SB03OU, XERBLA
C .. Intrinsic Functions ..
INTRINSIC ABS, DBLE, MAX, MIN, SQRT
C .. Executable Statements ..
C
DISCR = LSAME( DICO, 'D' )
LEFTW = LSAME( WEIGHT, 'L' ) .OR. LSAME( WEIGHT, 'B' )
RIGHTW = LSAME( WEIGHT, 'R' ) .OR. LSAME( WEIGHT, 'B' )
FRWGHT = LEFTW .OR. RIGHTW
C
INFO = 0
LW = 1
NNV = N + NV
NNW = N + NW
IF( LEFTW .AND. PV.GT.0 ) THEN
LW = MAX( LW, NNV*( NNV + MAX( NNV, PV ) + 5 ) )
ELSE
LW = MAX( LW, N*( P + 5 ) )
END IF
IF( RIGHTW .AND. MW.GT.0 ) THEN
LW = MAX( LW, NNW*( NNW + MAX( NNW, MW ) + 5 ) )
ELSE
LW = MAX( LW, N*( M + 5 ) )
END IF
C
IF( .NOT. ( LSAME( DICO, 'C' ) .OR. DISCR ) ) THEN
INFO = -1
ELSE IF( .NOT.( LSAME( JOBC, 'S' ) .OR. LSAME( JOBC, 'E' ) ) )
$ THEN
INFO = -2
ELSE IF( .NOT.( LSAME( JOBO, 'S' ) .OR. LSAME( JOBO, 'E' ) ) )
$ THEN
INFO = -3
ELSE IF( .NOT.( FRWGHT .OR. LSAME( WEIGHT, 'N' ) ) ) THEN
INFO = -4
ELSE IF( N.LT.0 ) THEN
INFO = -5
ELSE IF( M.LT.0 ) THEN
INFO = -6
ELSE IF( P.LT.0 ) THEN
INFO = -7
ELSE IF( NV.LT.0 ) THEN
INFO = -8
ELSE IF( PV.LT.0 ) THEN
INFO = -9
ELSE IF( NW.LT.0 ) THEN
INFO = -10
ELSE IF( MW.LT.0 ) THEN
INFO = -11
ELSE IF( ABS( ALPHAC ).GT.ONE ) THEN
INFO = -12
ELSE IF( ABS( ALPHAO ).GT.ONE ) THEN
INFO = -13
ELSE IF( LDA.LT.MAX( 1, N ) ) THEN
INFO = -15
ELSE IF( LDB.LT.MAX( 1, N ) ) THEN
INFO = -17
ELSE IF( LDC.LT.MAX( 1, P ) ) THEN
INFO = -19
ELSE IF( LDAV.LT.1 .OR. ( LEFTW .AND. LDAV.LT.NV ) ) THEN
INFO = -21
ELSE IF( LDBV.LT.1 .OR. ( LEFTW .AND. LDBV.LT.NV ) ) THEN
INFO = -23
ELSE IF( LDCV.LT.1 .OR. ( LEFTW .AND. LDCV.LT.PV ) ) THEN
INFO = -25
ELSE IF( LDDV.LT.1 .OR. ( LEFTW .AND. LDDV.LT.PV ) ) THEN
INFO = -27
ELSE IF( LDAW.LT.1 .OR. ( RIGHTW .AND. LDAW.LT.NW ) ) THEN
INFO = -29
ELSE IF( LDBW.LT.1 .OR. ( RIGHTW .AND. LDBW.LT.NW ) ) THEN
INFO = -31
ELSE IF( LDCW.LT.1 .OR. ( RIGHTW .AND. LDCW.LT.M ) ) THEN
INFO = -33
ELSE IF( LDDW.LT.1 .OR. ( RIGHTW .AND. LDDW.LT.M ) ) THEN
INFO = -35
ELSE IF( LDS.LT.MAX( 1, N ) ) THEN
INFO = -39
ELSE IF( LDR.LT.MAX( 1, N ) ) THEN
INFO = -41
ELSE IF( LDWORK.LT.LW ) THEN
INFO = -43
END IF
C
IF( INFO.NE.0 ) THEN
C
C Error return.
C
CALL XERBLA( 'AB09IY', -INFO )
RETURN
END IF
C
C Quick return if possible.
C
SCALEC = ONE
SCALEO = ONE
IF( MIN( N, M, P ).EQ.0 ) THEN
DWORK(1) = ONE
RETURN
END IF
C
WORK = 1
IF( LEFTW .AND. PV.GT.0 ) THEN
C
C Build the extended permuted matrices
C
C Ao = ( Av Bv*C ) , Co = ( Cv Dv*C ) .
C ( 0 A )
C
KAW = 1
KU = KAW + NNV*NNV
LDU = MAX( NNV, PV )
CALL DLACPY( 'Full', NV, NV, AV, LDAV, DWORK(KAW), NNV )
CALL DLASET( 'Full', N, NV, ZERO, ZERO, DWORK(KAW+NV), NNV )
CALL DGEMM( 'No-transpose', 'No-transpose', NV, N, P, ONE,
$ BV, LDBV, C, LDC, ZERO, DWORK(KAW+NNV*NV), NNV )
CALL DLACPY( 'Full', N, N, A, LDA, DWORK(KAW+NNV*NV+NV), NNV )
C
CALL DLACPY( 'Full', PV, NV, CV, LDCV, DWORK(KU), LDU )
CALL DGEMM( 'No-transpose', 'No-transpose', PV, N, P, ONE,
$ DV, LDDV, C, LDC, ZERO, DWORK(KU+LDU*NV), LDU )
C
C Solve for the Cholesky factor Ro of Qo, Qo = Ro'*Ro,
C the continuous-time Lyapunov equation (if DICO = 'C')
C
C Ao'*Qo + Qo*Ao + scaleo^2*Co'*Co = 0,
C
C or the discrete-time Lyapunov equation (if DICO = 'D')
C
C Ao'*Qo*Ao - Qo + scaleo^2*Co'*Co = 0.
C
C Workspace: need (N+NV)*(N+NV+MAX(N+NV,PV)+5);
C prefer larger.
C
KTAU = KU + LDU*NNV
KW = KTAU + NNV
C
CALL SB03OU( DISCR, .FALSE., NNV, PV, DWORK(KAW), NNV,
$ DWORK(KU), LDU, DWORK(KTAU), DWORK(KU), LDU,
$ SCALEO, DWORK(KW), LDWORK-KW+1, IERR )
C
IF( IERR.NE.0 ) THEN
INFO = 1
RETURN
END IF
WORK = MAX( WORK, DWORK(KW) + DBLE( KW - 1 ) )
C
C Partition Ro as Ro = ( R11 R12 ) and compute R such that
C ( 0 R22 )
C
C R'*R = R22'*R22 + (1-ALPHAO**2)*R12'*R12.
C
KW = KU + LDU*NV + NV
CALL DLACPY( 'Upper', N, N, DWORK(KW), LDU, R, LDR )
IF( ALPHAO.NE.ZERO ) THEN
T = SQRT( ONE - ALPHAO*ALPHAO )
DO 10 J = KU + LDU*NV, KU + LDU*(NNV-1), LDU
CALL DSCAL( NV, T, DWORK(J), 1 )
10 CONTINUE
END IF
IF( ALPHAO.LT.ONE .AND. NV.GT.0 ) THEN
KTAU = 1
CALL MB04OD( 'Full', N, 0, NV, R, LDR, DWORK(KU+LDU*NV),
$ LDU, DUM, 1, DUM, 1, DWORK(KTAU), DWORK(KW) )
C
DO 30 J = 1, N
DWORK(J) = R(J,J)
DO 20 I = 1, J
IF ( DWORK(I).LT.ZERO ) R(I,J) = -R(I,J)
20 CONTINUE
30 CONTINUE
C
END IF
C
IF( LSAME( JOBO, 'E' ) .AND. ALPHAO.LT.ONE ) THEN
C
C Form Y = -A'*(R'*R)-(R'*R)*A if DICO = 'C', or
C Y = -A'*(R'*R)*A+(R'*R) if DICO = 'D'.
C
CALL DLACPY( 'Upper', N, N, R, LDR, DWORK(KU), N )
CALL MB01WD( DICO, 'Upper', 'No-transpose', 'Hessenberg', N,
$ -ONE, ZERO, R, LDR, DWORK(KAW+NNV*NV+NV), NNV,
$ DWORK(KU), N, IERR )
C
C Compute the eigendecomposition of Y as Y = Z*Sigma*Z'.
C
KU = N + 1
CALL DSYEV( 'Vectors', 'Upper', N, R, LDR, DWORK, DWORK(KU),
$ LDWORK-N, IERR )
IF( IERR.GT.0 ) THEN
INFO = 3
RETURN
END IF
WORK = MAX( WORK, DWORK(KU) + DBLE( N ) )
C
C Partition Sigma = (Sigma1,Sigma2), such that
C Sigma1 <= 0, Sigma2 > 0.
C Partition correspondingly Z = [Z1 Z2].
C
TOL = MAX( ABS( DWORK(1) ), ABS( DWORK(N) ) )
$ * DLAMCH( 'Epsilon')
C _
C Form C = [ sqrt(Sigma2)*Z2' ]
C
PCBAR = 0
DO 40 J = 1, N
IF( DWORK(J).GT.TOL ) THEN
CALL DSCAL( N, SQRT( DWORK(J) ), R(1,J), 1 )
CALL DCOPY( N, R(1,J), 1, DWORK(KU+PCBAR), N )
PCBAR = PCBAR + 1
END IF
40 CONTINUE
C
C Solve for the Cholesky factor R of Q, Q = R'*R,
C the continuous-time Lyapunov equation (if DICO = 'C')
C _ _
C A'*Q + Q*A + t^2*C'*C = 0,
C
C or the discrete-time Lyapunov equation (if DICO = 'D')
C _ _
C A'*Q*A - Q + t^2*C'*C = 0.
C
C Workspace: need N*(N + 6);
C prefer larger.
C
KTAU = KU + N*N
KW = KTAU + N
C
CALL SB03OU( DISCR, .FALSE., N, PCBAR, A, LDA, DWORK(KU), N,
$ DWORK(KTAU), R, LDR, T, DWORK(KW), LDWORK-KW+1,
$ IERR )
IF( IERR.NE.0 ) THEN
INFO = 1
RETURN
END IF
SCALEO = SCALEO*T
WORK = MAX( WORK, DWORK(KW) + DBLE( KW - 1 ) )
END IF
C
ELSE
C
C Solve for the Cholesky factor R of Q, Q = R'*R,
C the continuous-time Lyapunov equation (if DICO = 'C')
C
C A'*Q + Q*A + scaleo^2*C'*C = 0,
C
C or the discrete-time Lyapunov equation (if DICO = 'D')
C
C A'*Q*A - Q + scaleo^2*C'*C = 0.
C
C Workspace: need N*(P + 5);
C prefer larger.
C
KU = 1
KTAU = KU + P*N
KW = KTAU + N
C
CALL DLACPY( 'Full', P, N, C, LDC, DWORK(KU), P )
CALL SB03OU( DISCR, .FALSE., N, P, A, LDA, DWORK(KU), P,
$ DWORK(KTAU), R, LDR, SCALEO, DWORK(KW),
$ LDWORK-KW+1, IERR )
IF( IERR.NE.0 ) THEN
INFO = 1
RETURN
END IF
WORK = MAX( WORK, DWORK(KW) + DBLE( KW - 1 ) )
END IF
C
IF( RIGHTW .AND. MW.GT.0 ) THEN
C
C Build the extended matrices
C
C Ai = ( A B*Cw ) , Bi = ( B*Dw ) .
C ( 0 Aw ) ( Bw )
C
KAW = 1
KU = KAW + NNW*NNW
CALL DLACPY( 'Full', N, N, A, LDA, DWORK(KAW), NNW )
CALL DLASET( 'Full', NW, N, ZERO, ZERO, DWORK(KAW+N), NNW )
CALL DGEMM( 'No-transpose', 'No-transpose', N, NW, M, ONE,
$ B, LDB, CW, LDCW, ZERO, DWORK(KAW+NNW*N), NNW )
CALL DLACPY( 'Full', NW, NW, AW, LDAW,
$ DWORK(KAW+NNW*N+N), NNW )
C
CALL DGEMM( 'No-transpose', 'No-transpose', N, MW, M, ONE,
$ B, LDB, DW, LDDW, ZERO, DWORK(KU), NNW )
CALL DLACPY( 'Full', NW, MW, BW, LDBW, DWORK(KU+N), NNW )
C
C Solve for the Cholesky factor Si of Pi, Pi = Si*Si',
C the continuous-time Lyapunov equation (if DICO = 'C')
C
C Ai*Pi + Pi*Ai' + scalec^2*Bi*Bi' = 0,
C
C or the discrete-time Lyapunov equation (if DICO = 'D')
C
C Ai*Pi*Ai' - Pi + scalec^2*Bi*Bi' = 0.
C
C Workspace: need (N+NW)*(N+NW+MAX(N+NW,MW)+5);
C prefer larger.
C
KTAU = KU + NNW*MAX( NNW, MW )
KW = KTAU + NNW
C
CALL SB03OU( DISCR, .TRUE., NNW, MW, DWORK(KAW), NNW,
$ DWORK(KU), NNW, DWORK(KTAU), DWORK(KU), NNW,
$ SCALEC, DWORK(KW), LDWORK-KW+1, IERR )
C
IF( IERR.NE.0 ) THEN
INFO = 2
RETURN
END IF
WORK = MAX( WORK, DWORK(KW) + DBLE( KW - 1 ) )
C
C Partition Si as Si = ( S11 S12 ) and compute S such that
C ( 0 S22 )
C
C S*S' = S11*S11' + (1-ALPHAC**2)*S12*S12'.
C
CALL DLACPY( 'Upper', N, N, DWORK(KU), NNW, S, LDS )
IF( ALPHAC.NE.ZERO ) THEN
T = SQRT( ONE - ALPHAC*ALPHAC )
DO 50 J = KU + NNW*N, KU + NNW*(NNW-1), NNW
CALL DSCAL( N, T, DWORK(J), 1 )
50 CONTINUE
END IF
IF( ALPHAC.LT.ONE .AND. NW.GT.0 ) THEN
KTAU = N*NNW + 1
KW = KTAU + N
CALL MB04ND( 'Full', N, 0, NW, S, LDS, DWORK(KU+NNW*N), NNW,
$ DUM, 1, DUM, 1, DWORK(KTAU), DWORK(KW) )
C
DO 70 J = 1, N
IF ( S(J,J).LT.ZERO ) THEN
DO 60 I = 1, J
S(I,J) = -S(I,J)
60 CONTINUE
END IF
70 CONTINUE
END IF
C
IF( LSAME( JOBC, 'E' ) .AND. ALPHAC.LT.ONE ) THEN
C
C Form X = -A*(S*S')-(S*S')*A' if DICO = 'C', or
C X = -A*(S*S')*A'+(S*S') if DICO = 'D'.
C
CALL DLACPY( 'Upper', N, N, S, LDS, DWORK(KU), N )
CALL MB01WD( DICO, 'Upper', 'Transpose', 'Hessenberg', N,
$ -ONE, ZERO, S, LDS, DWORK(KAW), NNW, DWORK(KU),
$ N, IERR )
C
C Compute the eigendecomposition of X as X = Z*Sigma*Z'.
C
KU = N + 1
CALL DSYEV( 'Vectors', 'Upper', N, S, LDS, DWORK, DWORK(KU),
$ LDWORK-N, IERR )
IF( IERR.GT.0 ) THEN
INFO = 3
RETURN
END IF
WORK = MAX( WORK, DWORK(KU) + DBLE( N ) )
C
C Partition Sigma = (Sigma1,Sigma2), such that
C Sigma1 =< 0, Sigma2 > 0.
C Partition correspondingly Z = [Z1 Z2].
C
TOL = MAX( ABS( DWORK(1) ), ABS( DWORK(N) ) )
$ * DLAMCH( 'Epsilon')
C _
C Form B = [ Z2*sqrt(Sigma2) ]
C
MBBAR = 0
I = KU
DO 80 J = 1, N
IF( DWORK(J).GT.TOL ) THEN
MBBAR = MBBAR + 1
CALL DSCAL( N, SQRT( DWORK(J) ), S(1,J), 1 )
CALL DCOPY( N, S(1,J), 1, DWORK(I), 1 )
I = I + N
END IF
80 CONTINUE
C
C Solve for the Cholesky factor S of P, P = S*S',
C the continuous-time Lyapunov equation (if DICO = 'C')
C _ _
C A*P + P*A' + t^2*B*B' = 0,
C
C or the discrete-time Lyapunov equation (if DICO = 'D')
C _ _
C A*P*A' - P + t^2*B*B' = 0.
C
C Workspace: need maximum N*(N + 6);
C prefer larger.
C
KTAU = KU + MBBAR*N
KW = KTAU + N
C
CALL SB03OU( DISCR, .TRUE., N, MBBAR, A, LDA, DWORK(KU), N,
$ DWORK(KTAU), S, LDS, T, DWORK(KW), LDWORK-KW+1,
$ IERR )
IF( IERR.NE.0 ) THEN
INFO = 2
RETURN
END IF
SCALEC = SCALEC*T
WORK = MAX( WORK, DWORK(KW) + DBLE( KW - 1 ) )
END IF
C
ELSE
C
C Solve for the Cholesky factor S of P, P = S*S',
C the continuous-time Lyapunov equation (if DICO = 'C')
C
C A*P + P*A' + scalec^2*B*B' = 0,
C
C or the discrete-time Lyapunov equation (if DICO = 'D')
C
C A*P*A' - P + scalec^2*B*B' = 0.
C
C Workspace: need N*(M+5);
C prefer larger.
C
KU = 1
KTAU = KU + N*M
KW = KTAU + N
C
CALL DLACPY( 'Full', N, M, B, LDB, DWORK(KU), N )
CALL SB03OU( DISCR, .TRUE., N, M, A, LDA, DWORK(KU), N,
$ DWORK(KTAU), S, LDS, SCALEC, DWORK(KW),
$ LDWORK-KW+1, IERR )
IF( IERR.NE.0 ) THEN
INFO = 2
RETURN
END IF
WORK = MAX( WORK, DWORK(KW) + DBLE( KW - 1 ) )
END IF
C
C Save optimal workspace.
C
DWORK(1) = WORK
C
RETURN
C *** Last line of AB09IY ***
END