Math-data integrated prediction model for ship maneuvering motion

Highly accurate motion prediction is critical to facilitate safe navigation and autonomous control of a ship. In this paper, a math-data integrated prediction (MDIP) model of ship maneuvering motion is newly developed by combining with mathematical and data-driven modules. The math part is identified by employing variable-order hydrodynamic derivatives which are derived from Taylor expansion. Using extended Kalman filter, an optimal-order mathematical prediction model is obtained. The data-driven part dwells on prediction residuals which are approximated by a least square-support vector machine. Furthermore, integration mechanisms are devised to cohere mathematical and data-driven models as a whole, by deploying summation and neural network approximation, respectively. By comparisons, it is verified that not only order selection but also math-data integration can enhance ship motion prediction accuracy, for which various maneuvering tests are analyzed. The results demonstrate that the proposed MDIP model using math-data integration offers much stronger generalization, thereby paving a new path for ship maneuvering motion prediction.

• Record URL:
  • https://doi.org/10.1016/j.oceaneng.2023.115255
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0029801823016396
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00298018
• Supplemental Notes:
  • © 2023 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Dong, Qi
  • 0009-0006-5816-1087
  • Wang, Ning
  • 0000-0003-1745-1425
  • Song, Jialin
  • 0009-0000-9817-6925
  • Hao, Lizhu
  • Liu, Shaoman
  • Han, Bing
  • Qu, Kai
• Publication Date: 2023-10-1

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: 115255
• Serial:
  • Ocean Engineering
  • Volume: 285
  • Issue Number: 0
  • Publisher: Pergamon
  • ISSN: 0029-8018
  • EISSN: 1873-5258
  • Serial URL: http://www.sciencedirect.com/science/journal/00298018

Subject/Index Terms

• TRT Terms: Data analysis; Maneuvering; Mathematical models; Predictive models; Ships
• Subject Areas: Data and Information Technology; Marine Transportation; Vehicles and Equipment;

Filing Info

• Accession Number: 01888169
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 19 2023 9:39AM