Adaptive NN control for a class of strict-feedback discrete-time nonlinear systems

被引：240
作者：
Ge, SS [1 ]
Li, GY [1 ]
Lee, TH [1 ]
机构：
[1] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 117576, Singapore
来源：
AUTOMATICA | 2003年 / 39卷 / 05期
关键词：
adaptive control; neural networks; discrete time; backstepping;
D O I：
10.1016/S0005-1098(03)00032-3
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：807 / 819
页数：13
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