Adaptive Integral Sliding Mode Control for a Class of Nonlinear Systems

Author

Liao, Daozheng ; Wang, Renming ; You, Wenxia ; Guo, Guilian

Author_Institution

Coll. of Electr. Eng. & Inf. Technol., China Three Gorges Univ., Yichang, China

fYear

2009

fDate

19-20 Dec. 2009

Firstpage

1

Lastpage

4

Abstract

This paper presents an adaptive control method for a class of nonlinear systems with matched uncertainties. Firstly, radial basis function neural networks is adopted to approximate the unknown system perturbance, then an robust adaptive control law is developed to stabilize the system based on the so-called integral sliding mode design approach. The reachability of the sliding surface and the convergence of the weight of the neural networks are showed by Lyapunov theory. Finally, some simulation studies are included to illustrate the effectiveness of the proposed method.

Keywords

Lyapunov methods; adaptive control; control system synthesis; neurocontrollers; nonlinear control systems; radial basis function networks; robust control; variable structure systems; Lyapunov theory; adaptive integral sliding mode control; convergence; matched uncertainties; nonlinear systems; radial basis function neural networks; robust adaptive control law; sliding surface; Adaptive control; Control systems; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control; Robust control; Sliding mode control; Surface treatment; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4994-1

Type

conf

DOI

10.1109/ICIECS.2009.5363342

Filename

5363342