Adaptive neural network control of helicopters with unknown dynamics

Shuzhi Sam Ge; Beibei Ren; Keng Peng Tee

doi:10.1109/cdc.2006.377693

Adaptive neural network control of helicopters with unknown dynamics

Shuzhi Sam Ge, Beibei Ren, Keng Peng Tee

Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

19 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 language	English
Title of host publication	Proceedings of the 45th IEEE Conference on Decision and Control 2006, CDC
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3022-3027
Number of pages	6
ISBN (Print)	1424401712, 9781424401710
DOIs	https://doi.org/10.1109/cdc.2006.377693
State	Published - 2006
Event	45th IEEE Conference on Decision and Control 2006, CDC - San Diego, CA, United States Duration: Dec 13 2006 → Dec 15 2006

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	45th IEEE Conference on Decision and Control 2006, CDC
Country/Territory	United States
City	San Diego, CA
Period	12/13/06 → 12/15/06

Access to Document

10.1109/cdc.2006.377693

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

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title = "Adaptive neural network control of helicopters with unknown dynamics",

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.",

author = "Ge, {Shuzhi Sam} and Beibei Ren and Tee, {Keng Peng}",

year = "2006",

doi = "10.1109/cdc.2006.377693",

language = "English",

isbn = "1424401712",

series = "Proceedings of the IEEE Conference on Decision and Control",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "3022--3027",

booktitle = "Proceedings of the 45th IEEE Conference on Decision and Control 2006, CDC",

note = "null ; Conference date: 13-12-2006 Through 15-12-2006",

}

Ge, SS, Ren, B & Tee, KP 2006, Adaptive neural network control of helicopters with unknown dynamics. in Proceedings of the 45th IEEE Conference on Decision and Control 2006, CDC., 4177843, Proceedings of the IEEE Conference on Decision and Control, Institute of Electrical and Electronics Engineers Inc., pp. 3022-3027, 45th IEEE Conference on Decision and Control 2006, CDC, San Diego, CA, United States, 12/13/06. https://doi.org/10.1109/cdc.2006.377693

Adaptive neural network control of helicopters with unknown dynamics. / Ge, Shuzhi Sam; Ren, Beibei; Tee, Keng Peng.

Proceedings of the 45th IEEE Conference on Decision and Control 2006, CDC. Institute of Electrical and Electronics Engineers Inc., 2006. p. 3022-3027 4177843 (Proceedings of the IEEE Conference on Decision and Control).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

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Adaptive neural network control of helicopters with unknown dynamics

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