Brief Fast approximate identification of nonlinear systems

Authors:
J. Schoukens;J. G. Nemeth;P. Crama;Y. Rolain;R. Pintelon
Affiliations:
Dep. ELEC, Vrije Universiteit Brussel, Pleinlaan 2, B1050 Brussels, Belgium;Dep. MIS, Budapest University of Technology & Economics, H-1521 Budapest, Hungary;Dep. ELEC, Vrije Universiteit Brussel, Pleinlaan 2, B1050 Brussels, Belgium;Dep. ELEC, Vrije Universiteit Brussel, Pleinlaan 2, B1050 Brussels, Belgium;Dep. ELEC, Vrije Universiteit Brussel, Pleinlaan 2, B1050 Brussels, Belgium
Venue:
Automatica (Journal of IFAC)
Year:
2003

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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.