AB13AD

Hankel-norm of a stable projection

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

Purpose

  To compute the Hankel-norm of the ALPHA-stable projection of the
  transfer-function matrix G of the state-space system (A,B,C).

Specification
      DOUBLE PRECISION FUNCTION AB13AD( DICO, EQUIL, N, M, P, ALPHA, A,
     $                                  LDA, B, LDB, C, LDC, NS, HSV,
     $                                  DWORK, LDWORK, INFO )
C     .. Scalar Arguments ..
      CHARACTER         DICO, EQUIL
      INTEGER           INFO, LDA, LDB, LDC, LDWORK, M, N, NS, P
      DOUBLE PRECISION  ALPHA
C     .. Array Arguments ..
      DOUBLE PRECISION  A(LDA,*), B(LDB,*), C(LDC,*), DWORK(*), HSV(*)

Function Value
  AB13AD  DOUBLE PRECISION
          The Hankel-norm of the ALPHA-stable projection of G
          (if INFO = 0).

Arguments

Mode Parameters

  DICO    CHARACTER*1
          Specifies the type of the 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.

Input/Output Parameters
  N       (input) INTEGER
          The order of the 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.

  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
          (see the Note below).

  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 N-by-N part of this
          array contains the state dynamics matrix A in a block
          diagonal real Schur form with its eigenvalues reordered
          and separated. The resulting A has two diagonal blocks.
          The leading NS-by-NS part of A has eigenvalues in the
          ALPHA-stability domain and the trailing (N-NS) x (N-NS)
          part has eigenvalues outside the ALPHA-stability domain.
          Note: The ALPHA-stability domain is defined either
                as the open half complex plane left to ALPHA,
                for a continous-time system (DICO = 'C'), or the
                interior of the ALPHA-radius circle centered in the
                origin, for a discrete-time system (DICO = 'D').

  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 N-by-M part of this
          array contains the input/state matrix B of the transformed
          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-N part of this
          array contains the state/output matrix C of the
          transformed system.

  LDC     INTEGER
          The leading dimension of array C.  LDC >= 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.

Workspace
  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(1,N*(MAX(N,M,P)+5)+N*(N+1)/2).
          For optimum 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 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.

Method
  Let be the following linear system

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

  where d[x(t)] is dx(t)/dt for a continuous-time system and x(t+1)
  for a discrete-time system, and let G be the corresponding
  transfer-function matrix. The following procedure is used to
  compute the Hankel-norm of the ALPHA-stable projection of G:

  1) Decompose additively G as

       G = G1 + G2

     such that G1 = (As,Bs,Cs) has only ALPHA-stable poles and
     G2 = (Au,Bu,Cu) has only ALPHA-unstable poles.
     For the computation of the additive decomposition, the
     algorithm presented in [1] is used.

  2) Compute the Hankel-norm of ALPHA-stable projection G1 as the
     the maximum Hankel singular value of the system (As,Bs,Cs).
     The computation of the Hankel singular values is performed
     by using the square-root method of [2].

References
  [1] Safonov, M.G., Jonckheere, E.A., Verma, M. and Limebeer, D.J.
      Synthesis of positive real multivariable feedback systems,
      Int. J. Control, Vol. 45, pp. 817-842, 1987.

  [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 method relies on a square-root technique.
                                  3
  The algorithms require about 17N  floating point operations.

Further Comments
  None
Example

Program Text

*     AB13AD 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
      PARAMETER        ( LDA = NMAX, LDB = NMAX, LDC = PMAX )
      INTEGER          LDWORK
      PARAMETER        ( LDWORK = NMAX*( MAX( NMAX, MMAX, PMAX ) + 5 )
     $                        + ( NMAX*( NMAX + 1 ) )/2 )
*     .. Local Scalars ..
      DOUBLE PRECISION ALPHA, SHNORM
      INTEGER          I, INFO, J, M, N, NS, P
      CHARACTER*1      DICO, EQUIL
*     .. Local Arrays ..
      DOUBLE PRECISION A(LDA,NMAX), B(LDB,MMAX), C(LDC,NMAX),
     $                 DWORK(LDWORK), HSV(NMAX)
*     .. External Functions ..
      DOUBLE PRECISION AB13AD
      EXTERNAL         AB13AD
*     .. Intrinsic Functions ..
      INTRINSIC        MAX
*     .. 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, ALPHA, DICO, EQUIL
      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 )
*              Compute the Hankel-norm of the ALPHA-stable projection of
*              (A,B,C).
               SHNORM = AB13AD( DICO, EQUIL, N, M, P, ALPHA, A, LDA, B,
     $                          LDB, C, LDC, NS, HSV, DWORK, LDWORK,
     $                          INFO)
*
               IF ( INFO.NE.0 ) THEN
                  WRITE ( NOUT, FMT = 99998 ) INFO
               ELSE
                  WRITE ( NOUT, FMT = 99997 ) SHNORM
                  WRITE ( NOUT, FMT = 99987 )
                  WRITE ( NOUT, FMT = 99995 ) ( HSV(J), J = 1,NS )
               END IF
            END IF
         END IF
      END IF
      STOP
*
99999 FORMAT (' AB13AD EXAMPLE PROGRAM RESULTS',/1X)
99998 FORMAT (' INFO on exit from AB13AD = ',I2)
99997 FORMAT (' The Hankel-norm of the ALPHA-projection = ',1PD14.5)
99995 FORMAT (20(1X,F8.4))
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-projection are')
      END
Program Data
 AB13AD EXAMPLE PROGRAM DATA (Continuous system)
  7  2  3   0.0  C  N
 -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
Program Results
 AB13AD EXAMPLE PROGRAM RESULTS

 The Hankel-norm of the ALPHA-projection =    2.51388D+00

 The Hankel singular values of ALPHA-projection are
   2.5139   2.0846   1.9178   0.7666   0.5473   0.0253   0.0246

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