Improved Genetic Algorithm-Based Optimization of Fuzzy Logic Controllers

This paper presents a new method to improve genetic algorithm-based optimization of fuzzy logic controllers considering both membership functions and rules. We indicate that eliminating the limitation on symmetric membership functions and rules results better optimization. Furthermore, we optimize fuzzy logic controller using genetic algorithm considering whole of system states, which cause the reliability of the controller to improve significantly.

کلیدواژه ها:

Fuzzy logic controller ، genetic algorithm ، optimization