DocumentCode :
2505048
Title :
Adaptive neuro sliding mode control of uncertain nonlinear system with dead zone input
Author :
Xu, Zibin ; Ruan, Jian ; Min, Jianqin
Author_Institution :
MOE Key Lab. of Mech. Manuf. & Autom., Zhejiang Univ. of Technol., Hangzhou
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
4723
Lastpage :
4726
Abstract :
Aiming at the uncertain nonlinear system with a dead zone input, a design method of adaptive neuro sliding mode control is presented to combine neural network theory with sliding mode control theory. RBF neural networks are used to realize modeling of nondeterministic system. Adaptive laws are derived based on Lyapunov stability theory which guarantees the stability of control system. Theoretical analysis and simulation results indicate that the control approach can be applied to the systems either with or without series nonlinearity and/or dead zone in the input.
Keywords :
Lyapunov methods; adaptive control; control system synthesis; neurocontrollers; nonlinear control systems; radial basis function networks; uncertain systems; variable structure systems; Lyapunov stability theory; RBF neural networks; adaptive neuro sliding mode control; dead zone input; design method; neural network theory; theoretical analysis; uncertain nonlinear system; Adaptive control; Adaptive systems; Control systems; Design methodology; Lyapunov method; Neural networks; Nonlinear systems; Programmable control; Sliding mode control; Stability; adaptive neuro sliding mode control; dead zone; sliding mode control; uncertain nonlinear system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
Type :
conf
DOI :
10.1109/WCICA.2008.4594533
Filename :
4594533
Link To Document :
بازگشت