Title
Reference Function Based Spatiotemporal Fuzzy Logic Control Design Using Support Vector Regression Learning.
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.
Year
DOI
Venue
2013
10.1155/2013/410279
JOURNAL OF APPLIED MATHEMATICS
Field
DocType
Volume
Nonlinear system,Expression (mathematics),Control theory,Support vector machine,Fuzzy logic,Equivalence (measure theory),Basis function,Fuzzy control system,Mathematics,Kernel (statistics)
Journal
2013
Issue
ISSN
Citations 
null
1110-757X
1
PageRank 
References 
Authors
0.35
9
4
Name
Order
Citations
PageRank
Xian-Xia Zhang111213.90
Ye Jiang210.35
Shiwei Ma313621.79
Bing Wang452.16