How to tune fuzzy controllers

Fuzzy controllers tuning implies the handling of a great quantity of variables like: the shape, number and ranges of the membership functions, the percentage of overlap among them and the design of the rule base. The problem is more complicated when it is necessary to control multivariable systems due that the number of parameters. The importance of the tuning problem implies to obtain fuzzy system that decrease the settling time of the processes in which it is applied, or in some cases, the settling time must be fixed to some specific value. In this work a very simple algorithm is presented for the tuning of a fuzzy controller using only one variable to adjust the performance of the system. The results would be obtained considering the relationship that exists between the membership functions and the settling time.

[1]  Piero P. Bonissone,et al.  Genetic algorithms for automated tuning of fuzzy controllers: a transportation application , 1996, Proceedings of IEEE 5th International Fuzzy Systems.

[2]  E. Cox,et al.  Fuzzy fundamentals , 1992, IEEE Spectrum.

[3]  Kazuo Asakawa,et al.  A prototype of neuro-fuzzy cooperation system , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[4]  Jie Zhang,et al.  Developing Robust Neural Network Models by Using Both Dynamic and Static Process Operating Data , 2001 .

[5]  E. Gomez-Ramirez,et al.  Stochastic learning control for nonlinear systems , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

[6]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..

[7]  Frank Klawonn,et al.  Modifications of genetic algorithms for designing and optimizing fuzzy controllers , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[8]  M.A. Lee,et al.  Integrating design stage of fuzzy systems using genetic algorithms , 1993, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems.

[9]  Edward T. Lee,et al.  Fuzzy Sets and Neural Networks , 1974 .

[10]  Francisco Herrera,et al.  Tuning fuzzy logic controllers by genetic algorithms , 1995, Int. J. Approx. Reason..