Intelligent Control of Induction Motor Using Hybrid System GA-PSO

This paper focuses on intelligent control of induction motor by hybrid system consisting of GA-PSO. Induction motor has been using in industrial area. However, it is challengeable on how we control effectively. From this point, an optimal solution using GA (Genetic Algorithm) and PSO (Particle Swarm Optimization) is introduced to intelligent control. In this case, it is possible to obtain local solution because chromosomes or individuals which have only a close affinity can convergent. To improve an optimal learning solution of control, This paper deal with applying PSO and Euclidian data distance to mutation procedure on GA's differentiation. Through this approaches, we can have global and local optimal solution together, and the faster and the exact optimal solution without any local solution. Four test functions are used for proof of this suggested algorithm.