Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0005-1098(03)00032-3
Title: Adaptive NN control for a class of strict-feedback discrete-time nonlinear systems
Authors: Ge, S.S. 
Li, G.Y.
Lee, T.H. 
Keywords: Adaptive control
Backstepping
Discrete time
Neural networks
Issue Date: May-2003
Source: Ge, S.S.,Li, G.Y.,Lee, T.H. (2003-05). Adaptive NN control for a class of strict-feedback discrete-time nonlinear systems. Automatica 39 (5) : 807-819. ScholarBank@NUS Repository. https://doi.org/10.1016/S0005-1098(03)00032-3
Abstract: In this paper, both full state and output feedback adaptive neural network (NN) controllers are presented for a class of strict-feedback discrete-time nonlinear systems. Firstly, Lyapunov-based full-state adaptive NN control is presented via backstepping, which avoids the possible controller singularity problem in adaptive nonlinear control and solves the noncausal problem in the discrete-time backstepping design procedure. After the strict-feedback form is transformed into a cascade form, another relatively simple Lyapunov-based direct output feedback control is developed. The closed-loop systems for both control schemes are proven to be semi-globally uniformly ultimately bounded. © 2003 Published by Elsevier Science Ltd.
Source Title: Automatica
URI: http://scholarbank.nus.edu.sg/handle/10635/54924
ISSN: 00051098
DOI: 10.1016/S0005-1098(03)00032-3
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