DocumentCode :
3550736
Title :
Neural network adaptive control for nonlinear uncertain dynamical systems with asymptotic stability guarantees
Author :
Hayakawa, Tomohisa ; Haddad, Wassim M. ; Hovakimyan, Naira
Author_Institution :
CREST, Japan Sci. & Technol. Agency, Saitama, Japan
fYear :
2005
fDate :
8-10 June 2005
Firstpage :
1301
Abstract :
A neuro adaptive control framework for nonlinear uncertain dynamical systems with input-to-state stable internal dynamics is developed. The proposed framework is Lyapunov-based and unlike standard neural network controllers guaranteeing ultimate boundedness, the framework guarantees partial asymptotic stability of the closed-loop system, that is, asymptotic stability with respect to part of the closed-loop system states associated with the system plant states. The neuro adaptive controllers are constructed without requiring explicit knowledge of the system dynamics other than the assumption that the plant dynamics are continuously differentiable and that the approximation error of uncertain system nonlinearities lie in a small gain-type norm bounded conic sector. This allows us to merge robust control synthesis tools with neural network adaptive control tools to guarantee system stability. Finally, an illustrative numerical example is provided to demonstrate the efficacy of the proposed approach.
Keywords :
Lyapunov methods; adaptive control; asymptotic stability; closed loop systems; control nonlinearities; control system synthesis; neurocontrollers; robust control; time-varying systems; uncertain systems; Lyapunov method; asymptotic stability; closed-loop system; input-to-state stable internal dynamics; neural network adaptive control; nonlinear uncertain dynamical system; robust control synthesis; uncertain system nonlinearities; Adaptive control; Approximation error; Asymptotic stability; Control nonlinearities; Control systems; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Programmable control; Uncertain systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 2005. Proceedings of the 2005
ISSN :
0743-1619
Print_ISBN :
0-7803-9098-9
Electronic_ISBN :
0743-1619
Type :
conf
DOI :
10.1109/ACC.2005.1470144
Filename :
1470144
Link To Document :
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