dc.contributor.author | Skulstad, Robert | |
dc.contributor.author | Li, Guoyuan | |
dc.contributor.author | Zhang, Houxiang | |
dc.contributor.author | Fossen, Thor I. | |
dc.date.accessioned | 2019-02-19T08:21:16Z | |
dc.date.available | 2019-02-19T08:21:16Z | |
dc.date.created | 2018-10-25T11:30:37Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | IFAC-PapersOnLine. 2018, 51 (29), 128-133. | nb_NO |
dc.identifier.issn | 2405-8963 | |
dc.identifier.uri | http://hdl.handle.net/11250/2586089 | |
dc.description.abstract | Dynamic Positioning (DP) of ships is a control mode that seeks to maintain a specific position (stationkeeping) or perform low-speed maneuvers. In this paper, a static Neural Network (NN) is proposed for control allocation of an over-actuated ship. The thruster force and commands are measured during a trial run of the simulated vessel to gather data for training of the NN. Then the network is trained and used to transform the virtual force commands from a motion controller into individual thruster commands. A standard Proportional Integral Derivative (PID) controller, using wave-filtered position and heading measurements, is implemented as motion controller for each Degree Of Freedom (DOF) of the ship. For a DP application the controllable DOFs are the translational motion in surge and sway directions, as well as the rotation about its up/down axis. Simulation tests were performed to verify the feasibility of this approach. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | International Federation of Automatic Control (IFAC) | nb_NO |
dc.title | A Neural Network Approach to Control Allocation of Ships for Dynamic Positioning | nb_NO |
dc.title.alternative | A Neural Network Approach to Control Allocation of Ships for Dynamic Positioning | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.description.version | publishedVersion | nb_NO |
dc.source.pagenumber | 128-133 | nb_NO |
dc.source.volume | 51 | nb_NO |
dc.source.journal | IFAC-PapersOnLine | nb_NO |
dc.source.issue | 29 | nb_NO |
dc.identifier.doi | 10.1016/j.ifacol.2018.09.481 | |
dc.identifier.cristin | 1623408 | |
dc.relation.project | Norges forskningsråd: 237929 | nb_NO |
dc.description.localcode | © 2018 IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. | nb_NO |
cristin.unitcode | 194,64,93,0 | |
cristin.unitcode | 194,63,25,0 | |
cristin.unitname | Institutt for havromsoperasjoner og byggteknikk | |
cristin.unitname | Institutt for teknisk kybernetikk | |
cristin.ispublished | true | |
cristin.fulltext | preprint | |
cristin.qualitycode | 1 | |