NDLI: Evolutionary computation approach to block oriented nonlinear model identification

Content Provider	IEEE Xplore Digital Library
Author	Hatanaka, T. Uosaki, K. Koga, M.
Copyright Year	2004
Description	Author affiliation: Dept. of Information & Phys. Sci., Osaka City Univ., Japan (Hatanaka, T.; Uosaki, K.)
Abstract	Wiener model and Hammerstein model are block oriented nonlinear models with the cascade connection of static non-linear part and linear dynamic part. Though they have very simple model structure, they can represent and approximate many real processes in electrical, chemical and biological engineering. In this paper, a novel approach for nonlinear system identification is addressed for the parameterized block oriented models such as Hammerstein and Wiener models. Approximating the nonlinear static part or its inverse by a piecewise linear function, its parameters are estimated by using the evolutionary computation approach such as genetic algorithm (GA) and evolution strategies (ES), while the linear dynamic system part is estimated by the least squares method. Numerical simulation studies illustrate the applicability of the proposed approach.
Starting Page	90
Ending Page	96
File Size	1037185
Page Count	7
File Format	PDF
ISBN	0780388739
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-07-20
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	ASCC
Subject Keyword	Parameter estimation Piecewise linear techniques Biological system modeling Piecewise linear approximation Chemical engineering Evolutionary computation Nonlinear dynamical systems Chemical processes Least squares approximation Nonlinear systems
Content Type	Text
Resource Type	Article

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