Speed control of induction motor using genetic algorithm based fuzzy controller

The fuzzy logic controller has been focused in the field of vector control of induction motors. However, a systematic method for designing and tuning the fuzzy logic controller is not developed yet. In this paper, an auto-tuning method for fuzzy logic controller based on the genetic algorithm is presented. In the proposed method, normalization parameters and membership function parameters of a fuzzy controller are translated into binary bit-strings, which are processed by the genetic algorithm in order to be optimized for the well-chosen objective function (i.e. fitness function). To examine the validity of the proposed method, a genetic algorithm based fuzzy controller for an indirect vector control of induction motors is simulated and an experiment is carried out. The simulation and experimental results show a significant enhancement in shortening development time and improving system performance over a traditional manually tuned fuzzy logic controller. Thus, in the case of changing motor, the proposed method is superior to a traditional method in the respect of development time and system performance.