NDLI: NN/RISE-based asymptotic tracking control of uncertain nonlinear systems

Content Provider	IEEE Xplore Digital Library
Author	Qinmin Yang Jagannathan, S. Youxian Sun
Copyright Year	2011
Description	Author affiliation: Department of Electrical and Computer Engineering, Missouri University of Science and Technology (formerly University of Missouri-Roll), 1870 Miner Circle, Rolla, 65409, USA (Jagannathan, S.) \|\| State Key Laboratory of Industrial Control Technology, Institute of Industrial Process Control, Zhejiang University, Hangzhou, 310027 China (Qinmin Yang; Youxian Sun)
Abstract	This paper presents a novel control methodology for the tracking control of a high-order continuous time nonlinear systems with unknown dynamics and external disturbance. The control signal consists of the robust integral of the sign of the error (RISE) feedback signal multiplied with an adaptive gain plus neural network (NN) output. The two-layer NN learns the system dynamics in an online manner while residual reconstruction errors and the external bounded system disturbances are overcome by the RISE signal. Semi-global asymptotic tracking performance is theoretically guaranteed by using the Lyapunov standard method, while the NN weights and all other signals are shown to be bounded. Further, simulations results are present to illustrate the control performance.
Starting Page	1361
Ending Page	1366
File Size	280667
Page Count	6
File Format	PDF
ISBN	9781457711046
ISSN	21589879
e-ISBN	9781457711039
DOI	10.1109/ISIC.2011.6045425
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Artificial neural networks Approximation methods Asymptotic stability Nonlinear systems Trajectory Stability analysis Robustness
Content Type	Text
Resource Type	Article

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