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dc.contributor.authorMehammer, Eirill Bachmann
dc.contributor.authorFøre, Martin
dc.contributor.authorSauder, Thomas Michel
dc.contributor.authorChabaud, Valentin Bruno
dc.contributor.authorParisini, Thomas
dc.date.accessioned2018-11-26T14:29:30Z
dc.date.available2018-11-26T14:29:30Z
dc.date.created2018-11-09T13:39:31Z
dc.date.issued2018
dc.identifier.citationJournal of Physics, Conference Series. 2018, 1104 .nb_NO
dc.identifier.issn1742-6588
dc.identifier.urihttp://hdl.handle.net/11250/2574912
dc.description.abstractOffshore wind power research is a rapidly growing field, because of the present climate crisis and increasing focus on renewable energy. Model testing plays an important role in the risk and cost analysis associated with offshore wind turbines (OWTs). The real-time hybrid model testing concept (ReaTHM testing) solves important challenges related to model testing of OWTs, such as achieving an accurate modelling of the wind field, and the occurrence of scaling issues when modelling wind and waves simultaneously. However, ReaTHM test set-ups are generally sensitive to noise, signal loss and inaccuracies in sensor values. The present study is focused on the design and implementation of a state estimator able to accurately estimate the position and velocity of floating structures, while taking disturbances into account. By combining the information received from several different sensors with mathematical models, the estimator provides smooth and reliable position and velocity estimates for ReaTHM testing applications. The main objective of the present study is to develop a kinematic state space model that could represent the motion of any floating structure in six degrees of freedom (6-DOF). The kinematic model is implemented in MATLAB, and acceleration time series obtained with numerical simulations are used as inputs. The computed outputs agree with the corresponding simulated motions. A Kalman estimator based on the state space model is designed, implemented and tested against virtual data from the numerical model, with artificially added disturbances. Sensitivity analyses addressing the robustness towards noise, time delays, signal loss and uncertainties are performed to identify the limits of the estimator. The estimator is demonstrated to be robust to most types of disturbances. Further, the state estimator is tested against physical data from laboratory experiments. Good agreement between the physically measured and the estimated states is observed.nb_NO
dc.description.abstractKalman estimation of position and velocity for ReaTHM testing applicationsnb_NO
dc.language.isoengnb_NO
dc.relation.urihttp://iopscience.iop.org/article/10.1088/1742-6596/1104/1/012008/meta
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleKalman estimation of position and velocity for ReaTHM testing applicationsnb_NO
dc.title.alternativeKalman estimation of position and velocity for ReaTHM testing applicationsnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.rights.holder© The Authors 2018. Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.nb_NO
dc.source.pagenumber10nb_NO
dc.source.volume1104nb_NO
dc.source.journalJournal of Physics, Conference Seriesnb_NO
dc.identifier.doi10.1088/1742-6596/1104/1/012008
dc.identifier.cristin1628715
dc.relation.projectNorges forskningsråd: 254845nb_NO
cristin.unitcode7566,2,0,0
cristin.unitcode7566,9,0,0
cristin.unitnameSjømatteknologi
cristin.unitnameSkip og havkonstruksjoner
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal