A New Method for Optimizing Fuzzy Membership Function

The successfulness of fuzzy application depends on a number of parameters, such as fuzzy membership functions, that are usually decided upon subjectively. In this paper, we propose a new method utilizing ant colony algorithm (ACA) to optimize the fuzzy membership function´s parameters, which overcoming the subjectivity and blindness in the process of designing the input or output membership functions. The fuzzy controller, which is optimized by ACA, is applied to a second order model and the simulation results shown a better result.