NDLI: Fuzzy system as parameter estimator of nonlinear dynamic functions

Content Provider	IEEE Xplore Digital Library
Author	Teng-Tiow Tay Surya Wahidin Tan
Copyright Year	1996
Abstract	In this paper we use adaptive fuzzy systems as intelligent identification systems for nonlinear time-varying plants. A new technique to design the fuzzy system that relies on the minimization of a loss function is presented. The design technique uses the centers of the fuzzy sets (labels) at the antecedent part of the rule base as the estimated parameters. This parametrization has the Linear In The Parameters (LITPs) characteristic that allows standard parameter estimation technique to be used to estimate the parameters of the fuzzy system. The combination of the fuzzy system and the estimation method then performs as a nonlinear estimator. If several fuzzy sets are defined for the input variables at the antecedent part, the fuzzy system ("fuzzy estimator") then behaves as a collection of nonlinear estimators where different rules' regions have different parameters. The proposed scheme is potentially capable of estimating the parameters of highly nonlinear plants. Simulation examples, which use plants with highly nonlinear gain, show the power of the proposed estimation scheme in comparison to estimation using the linear model.
Starting Page	313
Ending Page	326
Page Count	14
File Size	459684
File Format	PDF
ISSN	10834419
Volume Number	27
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1997-04-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy systems Parameter estimation Nonlinear dynamical systems Fuzzy sets Biological system modeling Biological control systems Input variables Power system modeling Nonlinear systems Adaptive systems
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Information Systems Electrical and Electronic Engineering Human-Computer Interaction Computer Science Applications Software

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