Identifying MIMO Wiener systems using subspace model identification methods

In this paper we show that the multivariable output-error state-space model (MOESP) class of sub-space model identification (SMI) schemes can be extended to identify Wiener systems, a series connection of a linear dynamic system followed by a static nonlinearity. In this paper, we restrict to present these extensions for the case the Taylor series expansion of the static nonlinearity contains odd terms. It is shown that the extension allows to identity the linear part of the Wiener systems as if the static nonlinearity is not present. In this way, it is related to cross-correlation analysis techniques.

[1]  Leon O. Chua,et al.  Fading memory and the problem of approximating nonlinear operators with volterra series , 1985 .

[2]  Patrick Dewilde,et al.  Subspace model identification Part 1. The output-error state-space model identification class of algorithms , 1992 .

[3]  M. Verhaegen.  Subspace model identification Part 2. Analysis of the elementary output-error state-space model identification algorithm , 1992 .

[4]  Michel Verhaegen,et al.  Application of a subspace model identification technique to identify LTI systems operating in closed-loop , 1993, Autom..

[5]  Bart De Moor,et al.  N4SID: Subspace algorithms for the identification of combined deterministic-stochastic systems , 1994, Autom..

[6]  K. Forsman,et al.  On nonlinear systems with linear dynamics , 1994, Proceedings of 1994 33rd IEEE Conference on Decision and Control.

[7]  David T. Westwick,et al.  Identification of Multiple-Input Nonlinear Systems Using Non-White Test Signals , 1994 .

[8]  Michel Verhaegen,et al.  Identification of the deterministic part of MIMO state space models given in innovations form from input-output data , 1994, Autom..

[9]  T. Wigren.  Convergence analysis of recursive identification algorithms based on the nonlinear Wiener model , 1994, IEEE Trans. Autom. Control..

[10]  M. Verhaegen,et al.  Some Experience with the MOESP Class of Subspace Model Identification Methods in Identifying the BO105 Helicopter , 1994 .

[11]  Michel Verhaegen,et al.  Identifying MIMO Wiener systems using subspace model identification methods , 1996, Signal Process..

[12]  M. Verhaegen,et al.  Identifying MIMO Hammerstein systems in the context of subspace model identification methods , 1996 .