Design of a Fuzzy Controller Using Genetic Algorithm Employing Simulated Annealing and Random Process

Simulated Annealing과 랜덤 프로세서가 적용된 유전 알고리즘을 이용한 퍼지 제어기의 설계

Traditional genetic algorithms, though robust, are generally not the most successful optimization algorithm on any particular domain. Hybridizing a genetic algorithm with other algorithms can produce better performance than both the genetic algorithm and the other algorithms. In this paper, we use random process and simulated annealing instead of mutation operator in order to get well tuned fuzzy rules. The key of this approach is to adjust both the width and the center of membership functions so that the tuned rule-based fuzzy controller can generate the desired performance. The effectiveness of the proposed algorithm is verified by computer simulation.