Identification of the parameters of the modified Lorentz function modelling hysteresis cycle

Abstract

This paper presents the use of a hybrid algorithm based on the artificial neural networks (ANN) and the genetic algorithms (GA) for the identification of the parameters of the modified Lorentz function from the measured cycles. The principle of the identification is based on the minimization of a function criterion which represents the difference between the measured and simulated cycles.