Discrete Time Nonlinear Identification via Recurrent High Order Neural Networks for a Three Phase Induction Motor

摘要

This paper deals with the problem of discrete-time nonlinear system identification via Recurrent High Order Neural Networks. It includes the respective stability analysis on the basis of the Lyapunov approach for the extended Kalman filter (EKF)-based NN training algorithm, which is applied for learning. Applicability of the scheme is illustrated via simulation for a discrete-time nonlinear model of an electric induction motor.