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Identification and control of marine vehicles using artificial intelligence techniques

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dc.contributor.advisor Flanagan, Colin
dc.contributor.advisor Toal, Daniel
dc.contributor.author van de Ven, Pepijn
dc.date.accessioned 2016-08-30T16:01:56Z
dc.date.available 2016-08-30T16:01:56Z
dc.date.issued 2005
dc.identifier.uri http://hdl.handle.net/10344/5170
dc.description peer-reviewed en_US
dc.description.abstract In this thesis a novel approach to the identification of marine craft dynamics using neural networks is described. From a literature review it emerged that augmented controllers, in which a conventional controller is augmenter with neural network, which accounts for unmodelled phenomena and/or unmodelled operation regions, are most likely to be used for future neural controller architectures. Such controllers are appealing, as neural networks can be used to identify the unknown phenomena with a high accuracy. However, at th ecurrent time, neural networks are predominantlz used to identify unknown phenomena in a lumped way. As a result, it is difficult, or even impossible, to use these neural networks in a conventional controller. A novel approach, involving the use of several neural networks for the identification of individual model parameters, is presented. The new approach is tested, first in simulations and consecutively in an experiment, and found to offer increased accuracy compared to a benchmark least squares identification method. Additionally, it is demonstrated that the obtained model can easily be reformulated in order to be used in a control scheme. In this control scheme, the learning capabilities of neural networks and the robustness and guaranteed stability of more conventional control schemes, can be combined, thus obtaining the advantages of both approaches. en_US
dc.language.iso eng en_US
dc.publisher University of Limerick
dc.subject identification en_US
dc.subject marine vehicles en_US
dc.subject neural networks en_US
dc.title Identification and control of marine vehicles using artificial intelligence techniques en_US
dc.type info:eu-repo/semantics/doctoralThesis en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.type.supercollection ul_theses_dissertations en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US


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