Adaptive practical finite-time stabilization for switched nonlinear systems in pure-feedback form

被引：44
|
作者：
Mao, Jun [1 ]
Huang, Shipei [1 ]
Xiang, Zhengrong [1 ]
机构：
[1] Nanjing Univ Sci & Technol, Sch Automat, Nanjing 210094, Jiangsu, Peoples R China
来源：
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2017年 / 354卷 / 10期
基金：
美国国家科学基金会;
关键词：
DYNAMIC SURFACE CONTROL; BACKSTEPPING CONTROLLER-DESIGN; FUZZY TRACKING CONTROL; STABILITY;
D O I：
10.1016/j.jfranklin.2017.03.018
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 investigates adaptive practical finite-time stabilization for a class of switched nonlinear systems in pure-feedback form. Under some appropriate assumptions, a controller and adaptive laws are designed by using adding a power integrator technique, and neural networks are employed to approximate unknown nonlinear functions. It is proved that all states of the closed-loop system converge to a small neighborhood of the origin in finite time. Finally, two simulations are provided to show the feasibility and validity of the proposed control scheme. (C) 2017 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：3971 / 3994
页数：24
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