Adaptive neural network control of helicopters with unknown dynamics

Shuzhi Sam Ge, Beibei Ren, Keng Peng Tee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations

Abstract

In this paper, adaptive neural network (NN) tracking control is considered for helicopters in the presence of parametric and functional uncertainties. Based on Lyapunov synthesis, the proposed adaptive NN control ensures that the system outputs track the given bounded reference signals to a small neighborhood of zero, and guarantees semiglobal uniformly ultimate boundedness (SGUUB) of all the closed-loop signals. The effectiveness of the proposed control is illustrated through extensive simulations.

Original languageEnglish
Title of host publicationProceedings of the 45th IEEE Conference on Decision and Control 2006, CDC
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3022-3027
Number of pages6
ISBN (Print)1424401712, 9781424401710
DOIs
StatePublished - 2006
Event45th IEEE Conference on Decision and Control 2006, CDC - San Diego, CA, United States
Duration: Dec 13 2006Dec 15 2006

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0191-2216

Conference

Conference45th IEEE Conference on Decision and Control 2006, CDC
CountryUnited States
CitySan Diego, CA
Period12/13/0612/15/06

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  • Cite this

    Ge, S. S., Ren, B., & Tee, K. P. (2006). Adaptive neural network control of helicopters with unknown dynamics. In Proceedings of the 45th IEEE Conference on Decision and Control 2006, CDC (pp. 3022-3027). [4177843] (Proceedings of the IEEE Conference on Decision and Control). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/cdc.2006.377693