DocumentCode :
2638589
Title :
Adaptive Feedback Control for a Class of Uncertain Nonlinear Systems with Dead-Zone
Author :
Chen, Mou ; Mei, Rong ; Chen, Wen-Hua
Author_Institution :
Autom. Coll., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing
fYear :
2008
fDate :
18-20 June 2008
Firstpage :
423
Lastpage :
423
Abstract :
In this paper, a robust adaptive feedback controller is proposed based on backstepping method and neural network for a class of uncertain nonlinear systems with deadzone. The subsystem uncertainty is approximated using radial basis function (RBF) neural network and weight value update law is given for approximating the subsystem uncertainty. Based on the output of the neural network, the robust adaptive control scheme is presented with backstepping method. The designed controller can not only guarantee robust stability of the uncertain nonlinear system, but also make it has L2-gain performance index which less than or equal to Gt 0.
Keywords :
adaptive control; feedback; neurocontrollers; nonlinear control systems; radial basis function networks; robust control; uncertain systems; L2-gain performance index; adaptive feedback control; backstepping method; dead-zone; radial basis function neural network; robust stability; subsystem uncertainty; uncertain nonlinear systems; Adaptive control; Backstepping; Design methodology; Feedback control; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control; Robust control; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on
Conference_Location :
Dalian, Liaoning
Print_ISBN :
978-0-7695-3161-8
Electronic_ISBN :
978-0-7695-3161-8
Type :
conf
DOI :
10.1109/ICICIC.2008.111
Filename :
4603612
Link To Document :
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