DocumentCode :
2261360
Title :
Adaptive Backstepping Control for a Class of Nonaffine Nonlinear Systems Based Neural Networks
Author :
Min, Jianqing ; Xu, Zibin ; Fang, Yingguo
Author_Institution :
Coll. of Biol. & Environ. Eng., Zhejiang Shuren Univ., Hangzhou
Volume :
1
fYear :
2008
fDate :
20-22 Dec. 2008
Firstpage :
716
Lastpage :
720
Abstract :
Aiming at a class of nonaffine nonlinear system with uncertainties, an adaptive backstepping neural controller design is presented. By applying backstepping design strategy and online approaching nonlinearity with fully tuned radial basis function (RBF) neural networks, the adaptive tuning rules are derived from the Lyapunov stability theory. A nonlinear tracking differentiator is introduced to deal with the problem of extremely expanded operation quantity of backstepping method. The developed control scheme guarantees that all the signals of the closed-loop system are uniformly ultimately bounded. The effectiveness of the proposed controller is illustrated through a simulation example.
Keywords :
Lyapunov methods; adaptive control; closed loop systems; control system synthesis; neurocontrollers; nonlinear control systems; radial basis function networks; stability; tracking; uncertain systems; Lyapunov stability theory; adaptive backstepping neural controller design; adaptive tuning rule; closed-loop system; neural network; nonaffine nonlinear control system; nonlinear tracking differentiator; radial basis function; uncertain system; Adaptive control; Adaptive systems; Backstepping; Control systems; Lyapunov method; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control; Uncertainty; adaptive control; backstepping; fully tuned RBF neural networks; nonaffine nonlinear system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3497-8
Type :
conf
DOI :
10.1109/IITA.2008.167
Filename :
4739665
Link To Document :
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