MAGNETIC HYSTERESIS MODELING VIA FEEDFORWARD NEURAL NETWORKS

A general neural approach to magnetic hysteresis modeling is proposed. The general memory storage properties of systems with rate independen t hysteresis are outlined. Thus, it is shown how it is possible to bui ld a neural hysteresis model based on feed-forward neural networks (NN 's) which fulfills these properties. The identification of the model c onsists in training the NN's by usual training algorithms such as back propagation. Finally, the proposed neural model has been tested by com paring its predictions with experimental data.