Identification of a Wiener–Hammerstein system using the polynomial nonlinear state space approach

Johan Paduart, Lieve Lauwers, Rik Pintelon, Joannes Schoukens

Research output: Contribution to journal › Article › peer-review

51 Citations (Scopus)

Abstract

In this paper, the Polynomial NonLinear State Space (PNLSS) approach is applied to model a nonlinear system with a Wiener-Hammerstein structure. To obtain good initial estimates, the best linear approximation of the system under test is first identified. Next, this linear model is extended to a polynomial nonlinear state space model to capture also the system's nonlinear behavior. The identification procedure is applied to measurement data
Original languageEnglish
Pages (from-to)1133-1139
Number of pages7
JournalControl Engineering Practice
Volume20
Publication statusPublished - 1 Nov 2012

Keywords

  • System identification
  • Wiener-Hammerstein systems
  • Best linear approximation
  • State space models

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  • DWTC282: Dynamical systems, control and optimization

    Pintelon, R. (Administrative Promotor), Vandewalle, J. (Co-Promotor), Aeyels, D. (Co-Promotor), Sepulchre, R. (Co-Promotor), Kinnaert, M. (Co-Promotor), Vande Wouwer, A. (Co-Promotor), Blondel, V. (Coördinator), Winkin, J. (Co-Promotor), Boyd, S. (Co-Promotor) & Leonard, N. (Co-Promotor)

    1/04/12 → 30/09/17

    Project: Fundamental

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