A general approach for hysteresis modeling and identification using neural networks

In this paper, we will present an approach to identify hysteresis using a slope sensitive neural network and a modified Luenberger observer. Identification is based on a general model of hysteresis without the need of internal states. Our identification approach provides mathematically stable adaptation and has shown excellent simulation results for various types of hysteresis.