AB09ED

Optimal Hankel-norm approximation based model reduction for unstable systems

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

Purpose

  To compute a reduced order model (Ar,Br,Cr,Dr) for an original
  state-space representation (A,B,C,D) by using the optimal
  Hankel-norm approximation method in conjunction with square-root
  balancing for the ALPHA-stable part of the system.

Specification
      SUBROUTINE AB09ED( DICO, EQUIL, ORDSEL, N, M, P, NR, ALPHA,
     $                   A, LDA, B, LDB, C, LDC, D, LDD, NS, HSV, TOL1,
     $                   TOL2, IWORK, DWORK, LDWORK, IWARN, INFO )
C     .. Scalar Arguments ..
      CHARACTER         DICO, EQUIL, ORDSEL
      INTEGER           INFO, IWARN, LDA, LDB, LDC, LDD, LDWORK,
     $                  M, N, NR, NS, P
      DOUBLE PRECISION  ALPHA, TOL1, TOL2
C     .. Array Arguments ..
      INTEGER           IWORK(*)
      DOUBLE PRECISION  A(LDA,*), B(LDB,*), C(LDC,*), D(LDD,*),
     $                  DWORK(*), HSV(*)

Arguments

Mode Parameters

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

  EQUIL   CHARACTER*1
          Specifies whether the user wishes to preliminarily
          equilibrate the triplet (A,B,C) as follows:
          = 'S':  perform equilibration (scaling);
          = 'N':  do not perform equilibration.

  ORDSEL  CHARACTER*1
          Specifies the order selection method as follows:
          = 'F':  the resulting order NR is fixed;
          = 'A':  the resulting order NR is automatically determined
                  on basis of the given tolerance TOL1.

Input/Output Parameters
  N       (input) INTEGER
          The order of the original state-space representation, i.e.
          the order of the matrix A.  N >= 0.

  M       (input) INTEGER
          The number of system inputs.  M >= 0.

  P       (input) INTEGER
          The number of system outputs.  P >= 0.

  NR      (input/output) INTEGER
          On entry with ORDSEL = 'F', NR is the desired order of
          the resulting reduced order system.  0 <= NR <= N.
          On exit, if INFO = 0, NR is the order of the resulting
          reduced order model. For a system with NU ALPHA-unstable
          eigenvalues and NS ALPHA-stable eigenvalues (NU+NS = N),
          NR is set as follows: if ORDSEL = 'F', NR is equal to
          NU+MIN(MAX(0,NR-NU-KR+1),NMIN), where KR is the
          multiplicity of the Hankel singular value HSV(NR-NU+1),
          NR is the desired order on entry, and NMIN is the order
          of a minimal realization of the ALPHA-stable part of the
          given system; NMIN is determined as the number of Hankel
          singular values greater than NS*EPS*HNORM(As,Bs,Cs), where
          EPS is the machine precision (see LAPACK Library Routine
          DLAMCH) and HNORM(As,Bs,Cs) is the Hankel norm of the
          ALPHA-stable part of the given system (computed in
          HSV(1));
          if ORDSEL = 'A', NR is the sum of NU and the number of
          Hankel singular values greater than
          MAX(TOL1,NS*EPS*HNORM(As,Bs,Cs)).

  ALPHA   (input) DOUBLE PRECISION
          Specifies the ALPHA-stability boundary for the eigenvalues
          of the state dynamics matrix A. For a continuous-time
          system (DICO = 'C'), ALPHA <= 0 is the boundary value for
          the real parts of eigenvalues, while for a discrete-time
          system (DICO = 'D'), 0 <= ALPHA <= 1 represents the
          boundary value for the moduli of eigenvalues.
          The ALPHA-stability domain does not include the boundary.

  A       (input/output) DOUBLE PRECISION array, dimension (LDA,N)
          On entry, the leading N-by-N part of this array must
          contain the state dynamics matrix A.
          On exit, if INFO = 0, the leading NR-by-NR part of this
          array contains the state dynamics matrix Ar of the
          reduced order system in a real Schur form.
          The resulting A has a block-diagonal form with two blocks.
          For a system with NU ALPHA-unstable eigenvalues and
          NS ALPHA-stable eigenvalues (NU+NS = N), the leading
          NU-by-NU block contains the unreduced part of A
          corresponding to ALPHA-unstable eigenvalues.
          The trailing (NR+NS-N)-by-(NR+NS-N) block contains
          the reduced part of A corresponding to ALPHA-stable
          eigenvalues.

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

  B       (input/output) DOUBLE PRECISION array, dimension (LDB,M)
          On entry, the leading N-by-M part of this array must
          contain the original input/state matrix B.
          On exit, if INFO = 0, the leading NR-by-M part of this
          array contains the input/state matrix Br of the reduced
          order system.

  LDB     INTEGER
          The leading dimension of 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 original state/output matrix C.
          On exit, if INFO = 0, the leading P-by-NR part of this
          array contains the state/output matrix Cr of the reduced
          order system.

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

  D       (input/output) DOUBLE PRECISION array, dimension (LDD,M)
          On entry, the leading P-by-M part of this array must
          contain the original input/output matrix D.
          On exit, if INFO = 0, the leading P-by-M part of this
          array contains the input/output matrix Dr of the reduced
          order system.

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

  NS      (output) INTEGER
          The dimension of the ALPHA-stable subsystem.

  HSV     (output) DOUBLE PRECISION array, dimension (N)
          If INFO = 0, the leading NS elements of HSV contain the
          Hankel singular values of the ALPHA-stable part of the
          original system ordered decreasingly.
          HSV(1) is the Hankel norm of the ALPHA-stable subsystem.

Tolerances
  TOL1    DOUBLE PRECISION
          If ORDSEL = 'A', TOL1 contains the tolerance for
          determining the order of reduced system.
          For model reduction, the recommended value is
          TOL1 = c*HNORM(As,Bs,Cs), where c is a constant in the
          interval [0.00001,0.001], and HNORM(As,Bs,Cs) is the
          Hankel-norm of the ALPHA-stable part of the given system
          (computed in HSV(1)).
          If TOL1 <= 0 on entry, the used default value is
          TOL1 = NS*EPS*HNORM(As,Bs,Cs), where NS is the number of
          ALPHA-stable eigenvalues of A and EPS is the machine
          precision (see LAPACK Library Routine DLAMCH).
          This value is appropriate to compute a minimal realization
          of the ALPHA-stable part.
          If ORDSEL = 'F', the value of TOL1 is ignored.

  TOL2    DOUBLE PRECISION
          The tolerance for determining the order of a minimal
          realization of the ALPHA-stable part of the given system.
          The recommended value is TOL2 = NS*EPS*HNORM(As,Bs,Cs).
          This value is used by default if TOL2 <= 0 on entry.
          If TOL2 > 0, then TOL2 <= TOL1.

Workspace
  IWORK   INTEGER array, dimension (LIWORK)
          LIWORK = MAX(1,M),   if DICO = 'C';
          LIWORK = MAX(1,N,M), if DICO = 'D'.
          On exit, if INFO = 0, IWORK(1) contains NMIN, the order of
          the computed minimal realization.

  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 >= MAX( LDW1, LDW2 ), where
          LDW1 = N*(2*N + MAX(N,M,P) + 5) + N*(N+1)/2,
          LDW2 = N*(M+P+2) + 2*M*P + MIN(N,M) +
                 MAX( 3*M+1, MIN(N,M)+P ).
          For optimum performance LDWORK should be larger.

Warning Indicator
  IWARN   INTEGER
          = 0:  no warning;
          = 1:  with ORDSEL = 'F', the selected order NR is greater
                than NSMIN, the sum of the order of the
                ALPHA-unstable part and the order of a minimal
                realization of the ALPHA-stable part of the given
                system. In this case, the resulting NR is set equal
                to NSMIN.
          = 2:  with ORDSEL = 'F', the selected order NR is less
                than the order of the ALPHA-unstable part of the
                given system. In this case NR is set equal to the
                order of the ALPHA-unstable part.

Error Indicator
  INFO    INTEGER
          = 0:  successful exit;
          < 0:  if INFO = -i, the i-th argument had an illegal
                value;
          = 1:  the computation of the ordered real Schur form of A
                failed;
          = 2:  the separation of the ALPHA-stable/unstable diagonal
                blocks failed because of very close eigenvalues;
          = 3:  the computed ALPHA-stable part is just stable,
                having stable eigenvalues very near to the imaginary
                axis (if DICO = 'C') or to the unit circle
                (if DICO = 'D');
          = 4:  the computation of Hankel singular values failed;
          = 5:  the computation of stable projection in the
                Hankel-norm approximation algorithm failed;
          = 6:  the order of computed stable projection in the
                Hankel-norm approximation algorithm differs
                from the order of Hankel-norm approximation.

Method
  Let be the following linear system

       d[x(t)] = Ax(t) + Bu(t)
       y(t)    = Cx(t) + Du(t)                           (1)

  where d[x(t)] is dx(t)/dt for a continuous-time system and x(t+1)
  for a discrete-time system. The subroutine AB09ED determines for
  the given system (1), the matrices of a reduced order system

       d[z(t)] = Ar*z(t) + Br*u(t)
       yr(t)   = Cr*z(t) + Dr*u(t)                       (2)

  such that

  HSV(NR+NS-N) <= INFNORM(G-Gr) <= 2*[HSV(NR+NS-N+1)+...+HSV(NS)],

  where G and Gr are transfer-function matrices of the systems
  (A,B,C,D) and (Ar,Br,Cr,Dr), respectively, and INFNORM(G) is the
  infinity-norm of G.

  The following procedure is used to reduce a given G:

  1) Decompose additively G as

       G = G1 + G2

     such that G1 = (As,Bs,Cs,D) has only ALPHA-stable poles and
     G2 = (Au,Bu,Cu,0) has only ALPHA-unstable poles.

  2) Determine G1r, a reduced order approximation of the
     ALPHA-stable part G1.

  3) Assemble the reduced model Gr as

        Gr = G1r + G2.

  To reduce the ALPHA-stable part G1, the optimal Hankel-norm
  approximation method of [1], based on the square-root
  balancing projection formulas of [2], is employed.

References
  [1] Glover, K.
      All optimal Hankel norm approximation of linear
      multivariable systems and their L-infinity error bounds.
      Int. J. Control, Vol. 36, pp. 1145-1193, 1984.

  [2] Tombs M.S. and Postlethwaite I.
      Truncated balanced realization of stable, non-minimal
      state-space systems.
      Int. J. Control, Vol. 46, pp. 1319-1330, 1987.

Numerical Aspects
  The implemented methods rely on an accuracy enhancing square-root
  technique.
                                      3
  The algorithms require less than 30N  floating point operations.

Further Comments
  None
Example

Program Text

*     AB09ED EXAMPLE PROGRAM TEXT
*     Copyright (c) 2002-2017 NICONET e.V.
*
*     .. Parameters ..
      INTEGER          NIN, NOUT
      PARAMETER        ( NIN = 5, NOUT = 6 )
      INTEGER          NMAX, MMAX, PMAX
      PARAMETER        ( NMAX = 20, MMAX = 20, PMAX = 20 )
      INTEGER          LDA, LDB, LDC, LDD
      PARAMETER        ( LDA = NMAX, LDB = NMAX, LDC = PMAX,
     $                   LDD = PMAX )
      INTEGER          LIWORK
      PARAMETER        ( LIWORK = MAX( NMAX, MMAX ) )
      INTEGER          LDWORK
      PARAMETER        ( LDWORK = MAX( NMAX*( 2*NMAX +
     $                                        MAX( NMAX, MMAX, PMAX ) +
     $                                 5 ) + ( NMAX*( NMAX + 1 ) )/2,
     $                                 NMAX*( MMAX + PMAX + 2 ) +
     $                                 2*MMAX*PMAX + MIN( NMAX, MMAX ) +
     $                                 MAX( 3*MMAX + 1,
     $                                      MIN( NMAX, MMAX ) +
     $                                      PMAX ) ) )
*     .. Local Scalars ..
      DOUBLE PRECISION ALPHA, TOL1, TOL2
      INTEGER          I, INFO, IWARN, J, M, N, NR, NS, P
      CHARACTER*1      DICO, EQUIL, ORDSEL
*     .. Local Arrays ..
      DOUBLE PRECISION A(LDA,NMAX), B(LDB,MMAX), C(LDC,NMAX),
     $                 D(LDD,MMAX), DWORK(LDWORK), HSV(NMAX)
      INTEGER          IWORK(LIWORK)
*     .. External Subroutines ..
      EXTERNAL         AB09ED
*     .. Intrinsic Functions ..
      INTRINSIC        MAX, MIN
*     .. Executable Statements ..
*
      WRITE ( NOUT, FMT = 99999 )
*     Skip the heading in the data file and read the data.
      READ ( NIN, FMT = '()' )
      READ ( NIN, FMT = * ) N, M, P, NR, ALPHA, TOL1, TOL2,
     $                      DICO, EQUIL, ORDSEL
      IF ( N.LT.0 .OR. N.GT.NMAX ) THEN
         WRITE ( NOUT, FMT = 99990 ) N
      ELSE
         READ ( NIN, FMT = * ) ( ( A(I,J), J = 1,N ), I = 1,N )
         IF ( M.LT.0 .OR. M.GT.MMAX ) THEN
            WRITE ( NOUT, FMT = 99989 ) M
         ELSE
            READ ( NIN, FMT = * ) ( ( B(I,J), J = 1,M ), I = 1, N )
            IF ( P.LT.0 .OR. P.GT.PMAX ) THEN
               WRITE ( NOUT, FMT = 99988 ) P
            ELSE
               READ ( NIN, FMT = * ) ( ( C(I,J), J = 1,N ), I = 1,P )
               READ ( NIN, FMT = * ) ( ( D(I,J), J = 1,M ), I = 1,P )
*              Find a reduced ssr for (A,B,C,D).
               CALL AB09ED( DICO, EQUIL, ORDSEL, N, M, P, NR, ALPHA,
     $                      A, LDA, B, LDB, C, LDC, D, LDD, NS, HSV,
     $                      TOL1, TOL2, IWORK, DWORK, LDWORK,
     $                      IWARN, INFO )
*
               IF ( INFO.NE.0 ) THEN
                  WRITE ( NOUT, FMT = 99998 ) INFO
               ELSE
                  WRITE ( NOUT, FMT = 99997 ) NR
                  WRITE ( NOUT, FMT = 99987 )
                  WRITE ( NOUT, FMT = 99995 ) ( HSV(J), J = 1, NS )
                  IF( NR.GT.0 ) WRITE ( NOUT, FMT = 99996 )
                  DO 20 I = 1, NR
                     WRITE ( NOUT, FMT = 99995 ) ( A(I,J), J = 1,NR )
   20             CONTINUE
                  IF( NR.GT.0 ) WRITE ( NOUT, FMT = 99993 )
                  DO 40 I = 1, NR
                     WRITE ( NOUT, FMT = 99995 ) ( B(I,J), J = 1,M )
   40             CONTINUE
                  IF( NR.GT.0 ) WRITE ( NOUT, FMT = 99992 )
                  DO 60 I = 1, P
                     WRITE ( NOUT, FMT = 99995 ) ( C(I,J), J = 1,NR )
   60             CONTINUE
                  WRITE ( NOUT, FMT = 99991 )
                  DO 70 I = 1, P
                     WRITE ( NOUT, FMT = 99995 ) ( D(I,J), J = 1,M )
   70             CONTINUE
               END IF
            END IF
         END IF
      END IF
      STOP
*
99999 FORMAT (' AB09ED EXAMPLE PROGRAM RESULTS',/1X)
99998 FORMAT (' INFO on exit from AB09ED = ',I2)
99997 FORMAT (' The order of reduced model = ',I2)
99996 FORMAT (/' The reduced state dynamics matrix Ar is ')
99995 FORMAT (20(1X,F8.4))
99993 FORMAT (/' The reduced input/state matrix Br is ')
99992 FORMAT (/' The reduced state/output matrix Cr is ')
99991 FORMAT (/' The reduced input/output matrix Dr is ')
99990 FORMAT (/' N is out of range.',/' N = ',I5)
99989 FORMAT (/' M is out of range.',/' M = ',I5)
99988 FORMAT (/' P is out of range.',/' P = ',I5)
99987 FORMAT (/' The Hankel singular values of ALPHA-stable part are')
      END
Program Data
 AB09ED EXAMPLE PROGRAM DATA (Continuous system)
  7  2   3   0   -0.6D0 1.E-1  1.E-14 C  N  A  
 -0.04165  0.0000  4.9200  -4.9200  0.0000  0.0000  0.0000
 -5.2100  -12.500  0.0000   0.0000  0.0000  0.0000  0.0000
  0.0000   3.3300 -3.3300   0.0000  0.0000  0.0000  0.0000
  0.5450   0.0000  0.0000   0.0000 -0.5450  0.0000  0.0000
  0.0000   0.0000  0.0000   4.9200 -0.04165 0.0000  4.9200
  0.0000   0.0000  0.0000   0.0000 -5.2100 -12.500  0.0000
  0.0000   0.0000  0.0000   0.0000  0.0000  3.3300 -3.3300
  0.0000   0.0000
  12.500   0.0000
  0.0000   0.0000
  0.0000   0.0000
  0.0000   0.0000
  0.0000   12.500
  0.0000   0.0000
  1.0000   0.0000  0.0000   0.0000  0.0000  0.0000  0.0000
  0.0000   0.0000  0.0000   1.0000  0.0000  0.0000  0.0000
  0.0000   0.0000  0.0000   0.0000  1.0000  0.0000  0.0000
  0.0000  0.0000
  0.0000  0.0000
  0.0000  0.0000

Program Results
 AB09ED EXAMPLE PROGRAM RESULTS

 The order of reduced model =  5

 The Hankel singular values of ALPHA-stable part are
   1.9178   0.8621   0.7666   0.0336   0.0246

 The reduced state dynamics matrix Ar is 
  -0.5181  -1.1084   0.0000   0.0000   0.0000
   8.8157  -0.5181   0.0000   0.0000   0.0000
   0.0000   0.0000  -1.2769   7.3264   0.0000
   0.0000   0.0000  -0.6203  -1.2769   0.0000
   0.0000   0.0000   0.0000   0.0000  -1.5496

 The reduced input/state matrix Br is 
  -1.2837   1.2837
  -0.7522   0.7522
   3.2016   3.2016
  -0.7640  -0.7640
   1.3415  -1.3415

 The reduced state/output matrix Cr is 
  -0.1380  -0.6445  -0.6247  -2.0857  -0.8964
   0.6246   0.0196   0.0000   0.0000   0.6131
   0.1380   0.6445  -0.6247  -2.0857   0.8964

 The reduced input/output matrix Dr is 
   0.0168  -0.0168
   0.0008  -0.0008
  -0.0168   0.0168

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