Replacement strategies of genetic algorithm in parametric identification of induction motor

The paper presents the problem of parametric identification of induction motor mathematical model with the use of genetic algorithm (GA). The influence of population replacement strategy on the identification results is analyzed. The identified parameters of the model were determined as a result of minimization of performance index defined as the mean-square error of stator current and angular velocity. The experimental investigations were performed for induction motor powered from voltage inverter. The work deals with the problem of identification, tournament selection, operators of crossover and mutation, replacement strategies and stop criterion. The steady-state genetic algorithm was analyzed with regard to convergence and accuracy of the identification process and the time of numerical calculations.