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A neural network based adaptive control scheme for underwater vehicles with an observer
Xing ZW(邢志伟); Gao JS(高建树); Wang LW(王立文); Feng XS(封锡盛)
Department水下机器人研究室
Conference Name5th World Congress on Intelligent Control and Automation
Conference DateJune 15-19, 2004
Conference PlaceHangzhou. P.R. China
Author of SourceIEEE
Source PublicationProceedings of the 5th World Congress on Intelligent Control and Automation
PublisherIEEE
Publication PlaceNew York
2004
Pages4996-5000
Indexed ByEI
EI Accession number2004388367559
Contribution Rank2
ISBN 0-7803-8273-0
KeywordAdaptive Conlrol Neural Netnwrk Observer Underwater Vehicles
AbstractObserver-based Neural Network Adaptive Control Scheme (OBNC) for underwater vehicles is proposed in this paper. Three parts compose the scheme: output feedback control, neural network and sliding mode item. Where, the output feedback control is used to guarantee the stability of the system in initial phase, and the neural network is used to approximate the nonlinear dynamics of underwater vehicles and the sliding mode item is used to compensate and bate the disturbances coming from internal and external. A linear observer is designed to estimate the corresponding rate and the control system is designed with only position measurement. The stability conditions and attraction region of the proposed scheme is provided by using lyapunov-based approach. The effective of the proposed control scheme is demonstrated by pool experiment.
Language英语
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/9203
Collection水下机器人研究室
Affiliation1.Aviat. Ground Spec. Equip. Res. Base, Civil Aviation University of China, Binhai Airpot, Tianjin 300300, China
2.Underwater Robotics Research Group, Shenyang Institute of Automation, Shenyang 110016, China
Recommended Citation
GB/T 7714
Xing ZW,Gao JS,Wang LW,et al. A neural network based adaptive control scheme for underwater vehicles with an observer[C]//IEEE. New York:IEEE,2004:4996-5000.
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