Paper Info
Title
Adaptive practical finite-time stabilization for switched nonlinear systems in pure-feedback form.
Abstract
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.
Year
DOI
Venue
2017
10.1016/j.jfranklin.2017.03.018
Journal of the Franklin Institute
Field
DocType
Volume
Mathematical optimization,Control theory,Nonlinear system,Control theory,Integrator,Artificial neural network,Mathematics,Finite time
Journal
354
Issue
ISSN
Citations 
10
0016-0032
11
PageRank 
References 
Authors
0.53
24
3
Name
Order
Citations
PageRank
Jun Mao1112.56
Shipei Huang21538.50
Zhengrong Xiang3656.76