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Structure discrimination in block-oriented models using linear approximations: A theoretic framework

Journal Contribution - Journal Article

In this paper we show that it is possible to retrieve structural information about complex block-oriented nonlinear systems, starting from linear approximations of the nonlinear system around different setpoints. The key idea is to monitor the movements of the poles and zeros of the linearized models and to reduce the number of candidate models on the basis of these observations. Besides the well known open loop single branch Wiener-, Hammerstein-, and Wiener-Hammerstein systems, we also cover a number of more general structures like parallel (multi branch) Wiener-Hammerstein models, and closed loop block oriented models, including linear fractional representation (LFR) models.
Journal:  Automatica : the journal of IFAC, the International Federation of Automatic Control
ISSN: 0005-1098
Volume: 53
Pages: 225-234
Publication year:2015
Keywords:Block-oriented models, Wiener–Hammerstein systems, Parallel structures, Feedback structures, Linear approximations
  • ORCID: /0000-0003-0492-6137/work/83057625
  • ORCID: /0000-0001-7582-7246/work/69374069
  • ORCID: /0000-0003-2738-7914/work/69212069
  • Scopus Id: 84924166724
  • WoS Id: 000351961900028
CSS-citation score:2