Real Coded Genetic Algorithm for Jiles–Atherton Model Parameters Identification

Abstract

The parameters set of the Jiles-Atherton hysteresis model is identified by using a real coded genetic algorithm. The parameters identification is performed by minimizing the mean squared error between experimental and simulated magnetic field curves. The procedure is validated by comparing experimental and simulated results.