The Study Of Fuzzy Controller's Optimization Design Based On Genetic Algorithm

In this thesis, the Genetic Algorithm is mainly applied to optimize the fuzzy controller's design. Based on fundamentally theoretical studies about fuzzy control and genetic algorithm, and connected with the present condition of the fuzzy controller's design, a method of fuzzy controller's optimizing design is come up with. Every genetic operators, specially, mutation operator, have been improved in the paper, because of the particularity of fuzzy controller's parametric coding. In the coding process, scale factor, fuzzy-control rule and Subordination function are integrated to code in order to complete integral optimizing. Under the less controlling rules, the Genetic Algorithm is used to filtrate the fuzzy-control rule table that was created by optimizing, to obtain the single optimal fuzzy-control table. At last, this method was proved to be effective in the artificial experiment.