DocumentCode :
1574023
Title :
Robust design of adaptive neural controllers for unknown nonlinear systems
Author :
Liu, Ziqian ; Torres, Raul E. ; Kotinis, Miltiadis
Author_Institution :
Eng. Dept., State Univ. of New York Maritime Coll., Throggs Neck, NY, USA
fYear :
2010
Firstpage :
993
Lastpage :
996
Abstract :
In this paper, we extend our previous research results from the stabilization of dynamic neural networks to the stabilization of unknown nonlinear systems, and present an approach of H control for nonlinear systems via dynamic neural networks. The proposed H controller is intended to attenuate the adverse impact of modeling error, considered as a disturbance, to a prescribed level with stability margins. A numerical example demonstrates the performance of stabilizing control on an unstable unknown nonlinear system.
Keywords :
H control; adaptive control; neurocontrollers; nonlinear systems; robust control; H control; adaptive neural controllers; dynamic neural networks stability; modeling error; robust design; stability margins; unknown nonlinear systems; Adaptive control; Control systems; Error correction; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Programmable control; Robust control; Stability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems (MWSCAS), 2010 53rd IEEE International Midwest Symposium on
Conference_Location :
Seattle, WA
ISSN :
1548-3746
Print_ISBN :
978-1-4244-7771-5
Type :
conf
DOI :
10.1109/MWSCAS.2010.5548804
Filename :
5548804
Link To Document :
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