Error-Compensated Marginal Linearization Method for Modeling a Fuzzy System

Author

De-Gang Wang ; Chen, C. L. Philip ; Wen-Yan Song ; Hong-Xing Li

Author_Institution

Sch. of Control Sci. & Eng., Dalian Univ. of Technol., Dalian, China

Volume

23

Issue

1

fYear

2015

fDate

Feb. 2015

Firstpage

215

Lastpage

222

Abstract

In this paper, a novel Error-compensated MArginal LINEarization (EMALINE) fuzzy modeling method is proposed. This method models a group of data information to a piecewise linear fuzzy system with high accuracy within a given error bound. It is proved that the fuzzy system generalized by the EMALINE method possesses universal approximation capability for a class of nonlinear systems. In addition, the theoretical approximation error bounds of the fuzzy system generalized by the EMALINE method are established and proved. Theoretical and practical results indicate that the EMALINE has better approximation accuracy than those of previous approaches. Numerical examples are shown to illustrate the validity of the proposed approach.

Keywords

approximation theory; fuzzy control; fuzzy set theory; linear systems; piecewise linear techniques; EMALINE method; error-compensated marginal linearization fuzzy modeling method; fuzzy system modeling; nonlinear system; piecewise linear fuzzy system; universal approximation capability; Accuracy; Fuzzy systems; Least squares approximations; Mathematical model; Nonlinear systems; Piecewise linear approximation; Error-compensated marginal linearization (EMALINE) method; fuzzy system; nonlinear system; self-organization fuzzy systems; universal approximation;

fLanguage

English

Journal_Title

Fuzzy Systems, IEEE Transactions on

Publisher

ieee

ISSN

1063-6706

Type

jour

DOI

10.1109/TFUZZ.2014.2306952

Filename

6744595