Evolutionary design of fuzzy rule base for nonlinear system modeling and control

In designing fuzzy models and controllers, we encounter a major difficulty in the identification of an optimized fuzzy rule base, which is traditional ly achieved by a tedious trial-and-error process. This paper presents an ap proach to the evolutionary design of an optimal fuzzy rule base for modelin g and control, Evolutionary programming is used to simultaneously evolve th e structure and the parameter of fuzzy rule base for a given task. To check the effectiveness of the suggested approach, four numerical examples are e xamined. The performance of the identified fuzzy rule bases is demonstrated .