A class of hierarchical fuzzy systems with constraints on the fuzzy rules

This paper presents a class of hierarchical fuzzy systems where previous layer outputs are used not in IF-parts, but only in THEN-parts of the fuzzy rules of the current layer. The proposed scheme is shown to be a universal approximator to any real continuous function on a compact set if complete fuzzy sets are used in the IF-parts of the fuzzy rules with singleton fuzzifier and center average defuzzifier. From the example of ball-and-beam control system simulation, it is demonstrated that the proposed scheme approximates with high accuracy a model nonlinear controller with fewer fuzzy rules than a centralized fuzzy system, and its control performance is comparable to that of a nonlinear controller.

[1]  W. Rudin Principles of mathematical analysis , 1964 .

[2]  Jun Zhou,et al.  Hierarchical fuzzy control , 1991 .

[3]  P. Kokotovic,et al.  Nonlinear control via approximate input-output linearization: the ball and beam example , 1992 .

[4]  J. Buckley,et al.  Fuzzy input-output controllers are universal approximators , 1993 .

[5]  Jun Zhou,et al.  Adaptive hierarchical fuzzy controller , 1993, IEEE Trans. Syst. Man Cybern..

[6]  T. Fukuda,et al.  Self-tuning fuzzy modeling with adaptive membership function, rules, and hierarchical structure based on genetic algorithm , 1995 .

[7]  T. Fukuda,et al.  Structure organization of hierarchical fuzzy model using by genetic algorithm , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

[8]  Li-Xin Wang,et al.  A Course In Fuzzy Systems and Control , 1996 .

[9]  W. Brockmann,et al.  NetFAN-a structured adaptive fuzzy approach , 1996, Proceedings of International Conference on Neural Networks (ICNN'96).

[10]  D. Linkens,et al.  A hierarchical multivariable fuzzy controller for learning with genetic algorithms , 1996 .

[11]  O. Huwendiek,et al.  On the applicability of the NetFAN-approach to function approximation , 1997, Proceedings of 6th International Fuzzy Systems Conference.

[12]  Takeshi Furuhashi,et al.  Knowledge extraction from hierarchical fuzzy model obtained by fuzzy neural networks and genetic algorithm , 1997, Proceedings of International Conference on Neural Networks (ICNN'97).

[13]  Rainer Holve Investigation of automatic rule generation for hierarchical fuzzy systems , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).

[14]  F. Chung,et al.  Deriving multistage FNN models from Takagi and Sugeno's fuzzy systems , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).

[15]  Li-Xin Wang,et al.  Universal approximation by hierarchical fuzzy systems , 1998, Fuzzy Sets Syst..

[16]  Shohachiro Nakanishi,et al.  Functional Completeness of Hierarchical Fuzzy Modeling , 1998, Inf. Sci..

[17]  Takeshi Furuhashi,et al.  Uneven allocation of membership functions for hierarchical fuzzy modeling using genetic algorithm , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[18]  Li-Xin Wang,et al.  Analysis and design of hierarchical fuzzy systems , 1999, IEEE Trans. Fuzzy Syst..

[19]  W. Brockmann,et al.  Function approximation with decomposed fuzzy systems , 1999, Fuzzy Sets Syst..

[20]  Derek A. Linkens,et al.  Hierarchical rule-based and self-organizing fuzzy logic control for depth of anaesthesia , 1999, IEEE Trans. Syst. Man Cybern. Part C.

[21]  Ke Zeng,et al.  A comparative study on sufficient conditions for Takagi-Sugeno fuzzy systems as universal approximators , 2000, IEEE Trans. Fuzzy Syst..

[22]  Li-Xin Wang,et al.  A note on universal approximation by hierarchical fuzzy systems , 2000, Inf. Sci..

[23]  Jin S. Lee,et al.  Hierarchical Fuzzy Logic Scheme with Constraints on the Fuzzy Rule , 2001, Intell. Autom. Soft Comput..

[24]  Noboru Takagi,et al.  Hierarchical fuzzy modeling and jointly expandable functions , 2002, Int. J. Intell. Syst..

[25]  Jin S. Lee,et al.  Universal approximation by hierarchical fuzzy system with constraints on the fuzzy rule , 2002, Fuzzy Sets Syst..