New genetic-based approach to generate fuzzy rules from numerical data

Optimization of fuzzy logic controller by genetic algorithm is a very active research area. This paper develops a new genetic-based method to generate fuzzy rules from numerical data; the fuzzy rules and fuzzy membership functions can be optimized simultaneously in the algorithm. An application to truck backer-upper control is presented. The performance of this new method is compared with a non-optimized method, and shows that the new method has a better performance