Adaptive NN control of uncertain nonlinear pure-feedback systems

被引:468
作者
Ge, SS [1 ]
Wang, C [1 ]
机构
[1] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 117576, Singapore
关键词
adaptive neural control; uncertain pure-feedback system; backstepping;
D O I
10.1016/S0005-1098(01)00254-0
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper is concerned with the control of nonlinear pure-feedback Systems with unknown nonlinear functions. This problem is considered difficult to be dealt with in the control literature. mainly because that the triangular structure Of pure-feedback systems has no affine appearance of the variables to be used as virtual controls. To overcome this difficulty. implicit function theorem is firstly exploited to assert the existence of the continuous desired virtual controls. NN approximators are then used to approximate the continuous desired virtual controls and desired practical control. With mild assumptions on the partial derivatives of the unknown functions, the developed adaptive NN control schemes achieve semi-global uniform ultimate boundedness of all the signals in the closed-loop. The control performance of the closed-loop system is guaranteed by suitably choosing the design parameters. (C) 2002 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:671 / 682
页数:12
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