Title: Fast approximate identification of nonlinear systems
Authors: Schoukens, Joannes ×
Nemeth, JG
Crama, P
Rolain, Y
Pintelon, R #
Issue Date: Jul-2003
Publisher: Pergamon-elsevier science ltd
Series Title: Automatica vol:39 issue:7 pages:1267-1274
Abstract: In this paper, a method is presented to extend the classical identification methods for linear systems towards nonlinear modelling of linear systems that suffer from nonlinear distortions. A well chosen, general nonlinear model structure is proposed that is identified in a two-step procedure. First, a best linear approximation is identified using the classical linear identification methods. In the second step, the nonlinear extensions are identified with a linear least-squares method. The proposed model not only includes Wiener and Hammerstein systems, it is also suitable to model nonlinear feedback systems. The stability of the nonlinear model can be easily verified. The method is illustrated on experimental data. (C) 2003 Elsevier Science Ltd. All rights reserved.
ISSN: 0005-1098
Publication status: published
KU Leuven publication type: IT
Appears in Collections:ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics
× corresponding author
# (joint) last author

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