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2013 Reference Function Based Spatiotemporal Fuzzy Logic Control Design Using Support Vector Regression Learning
Xian-Xia Zhang, Ye Jiang, Shiwei Ma, Bing Wang
J. Appl. Math. 2013(SI16): 1-13 (2013). DOI: 10.1155/2013/410279

Abstract

This paper presents a reference function based 3D FLC design methodology using support vector regression (SVR) learning. The concept of reference function is introduced to 3D FLC for the generation of 3D membership functions (MF), which enhance the capability of the 3D FLC to cope with more kinds of MFs. The nonlinear mathematical expression of the reference function based 3D FLC is derived, and spatial fuzzy basis functions are defined. Via relating spatial fuzzy basis functions of a 3D FLC to kernel functions of an SVR, an equivalence relationship between a 3D FLC and an SVR is established. Therefore, a 3D FLC can be constructed using the learned results of an SVR. Furthermore, the universal approximation capability of the proposed 3D fuzzy system is proven in terms of the finite covering theorem. Finally, the proposed method is applied to a catalytic packed-bed reactor and simulation results have verified its effectiveness.

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Xian-Xia Zhang. Ye Jiang. Shiwei Ma. Bing Wang. "Reference Function Based Spatiotemporal Fuzzy Logic Control Design Using Support Vector Regression Learning." J. Appl. Math. 2013 (SI16) 1 - 13, 2013. https://doi.org/10.1155/2013/410279

Information

Published: 2013
First available in Project Euclid: 14 March 2014

zbMATH: 06950656
Digital Object Identifier: 10.1155/2013/410279

Rights: Copyright © 2013 Hindawi

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Vol.2013 • No. SI16 • 2013
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