Identification of Preisach hysteresis model parameters using genetic algorithms

Preisach model is widely used to characterize ferromagnetic material's hysteresis. Thus, it is necessary to identify its parameters in order to complete magnetic hysteresis modeling successfully. In this paper, a stochastic identification method, Genetic algorithm, is implemented. The procedure consists of the minimization of the error between measurements and program results. Obtained results are compared with the classical nonlinear least square identification method and experimental hysteresis of a fully-process non oriented Fe-3 wt%Si steel sheet.