Research on Optimization of Fuzzy Membership Function Based on Ant Colony Algorithm
Chang Jianghui, Zhao Yong-sheng, Wei Chongzhu · 2006
The successful application of fuzzy control depends on some subjectively decided parameters, such as fuzzy membership functions. In this paper, a new method utilizing Ant Colony Algorithm (ACA) was proposed to optimize the fuzzy membership function's parameters. The subjectivity and blindness were avoided by using this method in the process of designing the input and output membership function. The fuzzy controller optimized by ACA has been applied to control the shipping course and the simulation results show good control performance.