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dc.contributor.authorXu, Haitong
dc.contributor.authorHassani, Vahid
dc.contributor.authorHinostroza, Miguel
dc.contributor.authorSoares, C. Guedes
dc.date.accessioned2019-04-05T08:12:04Z
dc.date.available2019-04-05T08:12:04Z
dc.date.created2019-01-14T10:34:21Z
dc.date.issued2018
dc.identifier.isbn978-0-7918-5133-3
dc.identifier.urihttp://hdl.handle.net/11250/2593423
dc.description.abstractThe Least-square support vector machine (LS-SVM) is used to estimate the dynamic parameters of a nonlinear marine vessel steering model in real-time. First, manoeuvring tests are carried out based on a scaled free-running ship model. The parameters are estimated using standard LS-SVM and compared with the theoretical solutions. Then, an online version, a sequential least square support vector machine, is derived and used to estimate the parameters of vessel steering in real-time. The results are compared with the values estimated by standard LS-SVM with batched training data. By comparison, sequential least square support vector machine can dynamically estimate the parameters successfully, and it can be used for designing a dynamic model-based controller of marine vessels.nb_NO
dc.language.isoengnb_NO
dc.publisherASMEnb_NO
dc.relation.ispartofASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering - Volume 11B: Honoring Symposium for Professor Carlos Guedes Soares on Marine Technology and Ocean Engineering
dc.titleReal-Time Parameter Estimation of Nonlinear Vessel Steering Model Using Support Vector Machinenb_NO
dc.typeChapternb_NO
dc.description.versionpublishedVersionnb_NO
dc.identifier.doi10.1115/OMAE2018-78234
dc.identifier.cristin1655968
dc.relation.projectNorges forskningsråd: 223254nb_NO
dc.description.localcodeCopyright © 2018 by ASMEnb_NO
cristin.unitcode194,64,20,0
cristin.unitnameInstitutt for marin teknikk
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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