A neuro-fuzzy-based Preisach approach on hysteresis modeling

摘要

Most of the present identification techniques of the Preisach model rely on a fairly large amount of experimental data. This paper proposes a method that utilizes the available data in the major loop and omits the need of measuring the first-order reversal curves. The method models hysteresis by applying the classical Preisach model whose identification procedure is performed by the utility of neurofuzzy approximators. The method is applied to the prediction of cyclic minor loops of a soft magnetic composite. The simulation and measurement results show the good accuracy of the method and validate the proposed approach. (c) 2005 Elsevier B.V. All rights reserved.