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신경망 기반의 적응제어기를 이용한 AUV의 운동제어

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dc.contributor.author이계홍-
dc.contributor.author이판묵-
dc.contributor.author이상정-
dc.date.accessioned2021-08-03T07:41:47Z-
dc.date.available2021-08-03T07:41:47Z-
dc.date.issued2002-02-01-
dc.identifier.urihttps://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/1849-
dc.description.abstractThis paper presents a neural net based nonlinear adaptive controller for an autonomous underwater vehicle (AUV). AUV's dynamics are highly nonlinear and their hydrodynamic coefficients vary with different operational conditions, so it is necessary for the high performance control system of an AUV to have the capacities of learning and adapting to the change of the AUV's dynamics. In this paper a linearly parameterized neural network is used to approximate the uncertainties of the AUV's dynamics, and a sliding mode control is introduced to attenuate the effects of the neural network's reconstruction errors and the disturbances of AUV's dynamics. The presented controller is consist of three parallel schemes; linear feedback control, sliding mode control and neural network. Lyapunov theory is used to guarantee the asymptotic convergence of trajectory tracking errors and the neural network's weights errors. Numerical simulations for motion control of an AUV are performed to illustrate the effectiveness of the proposed techniques.-
dc.format.extent8-
dc.language한국어-
dc.language.isoKOR-
dc.publisher한국해양공학회-
dc.title신경망 기반의 적응제어기를 이용한 AUV의 운동제어-
dc.title.alternativeMotion Control of an AUV Using a Neural-Net based Adaptive Controller-
dc.typeArticle-
dc.publisher.location대한민국-
dc.identifier.bibliographicCitation한국해양공학회지, v.16, no.1, pp 8 - 15-
dc.citation.title한국해양공학회지-
dc.citation.volume16-
dc.citation.number1-
dc.citation.startPage8-
dc.citation.endPage15-
dc.description.isOpenAccessN-
dc.subject.keywordAuthorAdaptive Control-
dc.subject.keywordAuthorSliding Mode Control-
dc.subject.keywordAuthorNeural Network-
dc.subject.keywordAuthorFunctional Approximation-
dc.subject.keywordAuthorAUV-
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