Parameter Identification of Induction Motors by Imperialist Competitive Algorithm

In order to control induction motors effectively, an accurate parameter identification is needed. There are some prevalent methods for calculating parameters of equivalent circuit like blocked rotor test, no load test, DC test, analytical methods and etc. But, their most important defect is their inaccuracy in some applications. Then, to overcome this deficiency, some other identification methods have been proposed. This paper deals with a novel method in order to identify parameters of induction motors in an accurate manner. The proposed method is based on transient state of current and speed of motor and comparing it with simulation results in order to minimize the error between them. Results show that the imperialist competitive algorithm (ICA) has a good performance as an efficient optimization method which is used for parameter identification of motor and optimization purposes in contrast with some other identification methods like: particle swarm optimization (PSO), Bees algorithm (BA) and traditional tests.