Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/69207
Title: Adaptive NN control for a class of strict-feedback discrete-time nonlinear systems via backstepping
Authors: Ge, S.S. 
Li, G.Y.
Lee, T.H. 
Issue Date: 2001
Source: Ge, S.S.,Li, G.Y.,Lee, T.H. (2001). Adaptive NN control for a class of strict-feedback discrete-time nonlinear systems via backstepping. Proceedings of the IEEE Conference on Decision and Control 4 : 3146-3151. ScholarBank@NUS Repository.
Abstract: In this paper, the state feedback controller is studied for a class of strict-feedback discrete-time nonlinear systems in the presence of bounded disturbances. A Lyapunov-based full state feedback neural network control structure is presented via backstepping, which solves the noncausal problem in the discrete-time back-stepping design procedure. The closed-loop system is proven to be semi-globally uniformly ultimately bounded (SGUUB). An arbitrarily small tracking error can be achieved if the size of the neural network is chosen large enough, and the control performance of the closed-loop system is guaranteed by suitably choosing the design parameters.
Source Title: Proceedings of the IEEE Conference on Decision and Control
URI: http://scholarbank.nus.edu.sg/handle/10635/69207
ISSN: 01912216
Appears in Collections:Staff Publications

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