A Efficient Controller Design with Fuzzy Logic and Genetic Algorithms

퍼지 로직과 유전자 알고리즘을 이용한 효율적인 제어기 설계

Previous works using a Multi-population Genetic Algorithm have divided chromosome into two components, rule sets and membership functions. However, in this case bad rule sets disturb optimization in good rule sets and membership functions. A new method for a Multi-population Genetic Algorithm suggests three components, good rule sets, bad rule sets, and membership functions. To show the effectiveness of this method, fuzzy controller is applied in a Truck Backing Problem. Results of the computer simulation show good adaptation of the proposed method for a Multi-population Genetic Algorithm.