Automatic optimal design of fuzzy controllers based on genetic algorithms

Automatic design of fuzzy controller should optimize membership functions and the rule base at the same time. The method proposed in this paper is capable of solving these problems by means of genetic algorithms (GAs). A GA is an extremely powerful optimization technique that could be used to optimize the parameters of fuzzy controllers. To increase the efficiency of a genetic algorithm the influence of migration in a multilevel distributed GA (MDGA) is tested. MDGAs use the power of the computers better than one-level distributed GAs.