Parameter Estimation of Induction Motor Using Shuffled Frog Leaping and Imperialistic Competitive Algorithms

This paper presents two methods based on Shuffled Frog Leaping Algorithm (SFLA) and Imperialistic Competitive Algorithm (ICA) for determining the values of the steady-state equivalent circuit parameters of an induction motor. The parameter estimation procedure is based on minimizing the error between some manufacturer’s data and corresponding data calculated from proposed methods by determining proper objective functions. Proposed methods are applied to two different models of two distinct induction motors and the results are presented. Little errors between the manufacturer’s data and the corresponding calculated data, and also small values reached for the objective functions confirms the exactness of the estimation processes.