期刊
AUTOMATICA
卷 39, 期 5, 页码 807-819出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/S0005-1098(03)00032-3
关键词
adaptive control; neural networks; discrete time; backstepping
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. (C) 2003 Published by Elsevier Science Ltd.
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