RHONN identifier-control scheme for nonlinear discrete-time systems with unknown time-delays

• DOI: 10.1016/j.jfranklin.2017.11.014
• Publication Date: 2017-12-02T08:18:20Z
• Authors: Jorge D. Rios; Alma Y. Alanis; Carlos Lopez-Franco; Nancy Arana-Daniel
• Keywords: 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology

Abstract This work presents a neural identifier-control scheme for uncertain nonlinear discrete-time systems with unknown time-delays. This scheme is based on a neural identifier to get a model of the system and a discrete-time block control technique based on sliding modes to generate the control law. The neural identifier is based on a Recurrent High Order Neural Network (RHONN) trained with an Extended Kalman Filter (EKF) based algorithm. Applicability is shown using real-time test results for linear induction motors. Also, a Lyapunov analysis is added in order to prove the semi-globally uniformly ultimately boundedness (SGUUB) of the proposed neural identifier-control scheme.