PSO-based Evolutionary Optimization for Parameter Identification of an Induction Motor

In this paper a particle swarm optimization (PSO) algorithm with a constriction factor is applied to identify the parameters of an induction motor. The variables used to estimate electrical and mechanical parameters are the measured stator currents and voltages. Performance of the identification scheme is demonstrated through simulation and compared with parameters obtained with a nonlinear least square technique. The estimated parameters compare well with the actual parameters.