DocumentCode
2839104
Title
Robust output feedback control for a class of nonlinear systems by adaptive neural networks
Author
Long Lijun ; Xie Chengkang
Author_Institution
Sch. of Math. & Syst. Sci., Southwest Univ., Chongqing, China
fYear
2009
fDate
17-19 June 2009
Firstpage
4995
Lastpage
5000
Abstract
By Nussbaum-type gain technique and adaptive neural network, a robust adaptive neural network controller is established for a class of uncertain nonlinear systems. Under this controller, the output is regulated to a neighborhood of origin by appropriately choosing design parameters, and all signals of the closed-loop are kept bounded. The feasibility is investigated by an illustrative simulation example.
Keywords
feedback; nonlinear control systems; radial basis function networks; robust control; uncertain systems; adaptive neural networks; backstepping; radial basis function; robust output feedback control; uncertain nonlinear systems; Adaptive control; Adaptive systems; Control systems; Neural networks; Nonlinear control systems; Nonlinear systems; Output feedback; Programmable control; Robust control; Signal design; Backstepping; Neural Network; Output Feedback; Radial Basis Function;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location
Guilin
Print_ISBN
978-1-4244-2722-2
Electronic_ISBN
978-1-4244-2723-9
Type
conf
DOI
10.1109/CCDC.2009.5194933
Filename
5194933
Link To Document