DocumentCode :
3210518
Title :
Adaptive RBF NN-based controller design for a class of time-delay nonlinear systems
Author :
Xue Xiuli ; Yang Qing ; Li Shurong
Author_Institution :
Coll. of Inf. & Control Eng., China Univ. of Pet., Dongying, China
fYear :
2006
fDate :
7-11 Aug. 2006
Firstpage :
1118
Lastpage :
1122
Abstract :
In this paper, an adaptive neural controller for a class of strict-feedback time-delay nonlinear system with unknown time-delay is proposed. Based on a RBF neural network online approximation model, a state feedback adaptive controller is obtained by constructing a novel Lyapunov-Krasovskii functional. It´s shown that the proposed method guarantees the semiglobal boundedness of all signals in the adaptive closed-loop systems. A simulation example is provided to illustrate the validity of the proposed controller.
Keywords :
Lyapunov methods; adaptive control; approximation theory; closed loop systems; delays; neurocontrollers; nonlinear systems; radial basis function networks; state feedback; Lyapunov-Krasovskii functional; RBF neural network online approximation; adaptive closed-loop system; adaptive neural controller; state feedback adaptive controller; strict-feedback time-delay nonlinear system; Adaptive control; Control engineering; Control systems; Educational institutions; Neural networks; Nonlinear control systems; Nonlinear systems; Petroleum; Programmable control; State feedback; Lyapunov-Krasovskii functional; RBF neural network; adaptive control; time-delay nonlinear system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference, 2006. CCC 2006. Chinese
Conference_Location :
Harbin
Print_ISBN :
7-81077-802-1
Type :
conf
DOI :
10.1109/CHICC.2006.280574
Filename :
4060253
Link To Document :
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