Reference Function Based Spatiotemporal Fuzzy Logic Control Design Using Support Vector Regression Learning

摘要

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 3DFLCto cope withmore kinds ofMFs.The nonlinear mathematical expression of the reference function based 3D FLCis derived, and spatial fuzzy basis functions are defined.Via relating spatial fuzzy basis functions of a 3DFLCto 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.