Hopfield Neural Network Identification for Preisach Hysteresis System

A Hopfield neural network(HNN)identification approach is proposed for the hysteresis nonlinear system with Preisach model. Firstly, the Preisach model is applied and the designed HNN is transformed into matrix notation. Afterwards, two energy functions are proposed for the hysteresis system to estimate the unknown parameters. Finally, the detail of the identification is verified by constant and time-varying coefficients, and that the identification results are verified the effectiveness of the proposed approach.