Adaptive Neural Control for a Class of Perturbed Time-delay Nonlinear Systems

Author

Wang, Ruliang ; Li, Jie

Author_Institution

Comput. & Inf. Eng. Coll., Guangxi Teachers Educ. Univ., Nanning, China

fYear

2011

fDate

3-4 Dec. 2011

Firstpage

358

Lastpage

361

Abstract

In this paper, an adaptive neural control for a class of time-delay nonlinear systems with perturbed is posed, Based on radius basis function(RBF)neural networks, The radius basis function (RBF) neural networks is employed to estimate the unknown continuous functions. It is shown that the proposed method guarantees the semi-globally uniformly ultimately bounded ness of all signals in the adaptive closed-loop systems. Simulation results are provided to illustrate the performance of the proposed approach.

Keywords

adaptive control; closed loop systems; delays; neurocontrollers; nonlinear control systems; perturbation techniques; radial basis function networks; adaptive closed loop systems; adaptive neural control; perturbed time delay nonlinear systems; radius basis function neural networks; semiglobally uniformly ultimately boundedness; Adaptive systems; Delay; Educational institutions; Neural networks; Nonlinear systems; Robustness; Vectors; Adaptive control; Nonlinear; RBF neural networks; Time-delay;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Security (CIS), 2011 Seventh International Conference on

Conference_Location

Hainan

Print_ISBN

978-1-4577-2008-6

Type

conf

DOI

10.1109/CIS.2011.86

Filename

6128139