International Journal of Naval Architecture and Ocean Engineering

The Society of Naval Architects of Korea (대한조선학회)
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Motion predictive control for DPS using predicted drifted ship position based on deep learning and replay buffer

  • Lee, Daesoo (Division of Naval Architecture and Ocean Systems Engineering, Korea Maritime and Ocean University) ;
  • Lee, Seung Jae (Division of Naval Architecture and Ocean Systems Engineering, Korea Maritime and Ocean University)
  • Received : 2020.03.19
  • Accepted : 2020.09.20
  • Published : 2020.12.31
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Abstract

Typically, a Dynamic Positioning System (DPS) uses a PID feed-back system, and it often adopts a wind feed-forward system because of its easier implementation than a feed-forward system based on current or wave. But, because a ship's drifting motion is caused by wind, current, and wave drift loads, all three environmental loads should be considered. In this study, a motion predictive control for the PID feedback system of the DPS is proposed, which considers the three environmental loads by utilizing predicted drifted ship positions in the future since it contains information about the three environmental loads from the moment to the future. The prediction accuracy for the future drifted ship position is ensured by adopting deep learning algorithms and a replay buffer. Finally, it is shown that the proposed motion predictive system results in better station-keeping performance than the wind feed-forward system.

Keywords

Acknowledgement

This material is based upon work supported by the Ministry of Trade, Industry & Energy (MOTIE, Korea) under Industrial Technology Innovation Program. No. 10063405, 'Development of hull form of year-round floatingetype offshore structure based on the Arctic Ocean in ARC7 condition with dynamic positioning and mooring system'

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