Adaptive online modeling of ship maneuvering motion based on error monitoring
ObjectiveAiming to address the problem of model inaccuracy caused by ship dynamic changes during actual navigation, this study proposes an adaptive online modeling method for ship maneuvering motion based on an error monitoring mechanism. MethodsThe method determines model update timing through a mo...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Editorial Office of Chinese Journal of Ship Research
2025-02-01
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| Series: | Zhongguo Jianchuan Yanjiu |
| Subjects: | |
| Online Access: | http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.04019 |
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| _version_ | 1850240475452145664 |
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| author | Yaohui YU Suyang LIU Zihao WANG Wenbo XIE Yan PENG |
| author_facet | Yaohui YU Suyang LIU Zihao WANG Wenbo XIE Yan PENG |
| author_sort | Yaohui YU |
| collection | DOAJ |
| description | ObjectiveAiming to address the problem of model inaccuracy caused by ship dynamic changes during actual navigation, this study proposes an adaptive online modeling method for ship maneuvering motion based on an error monitoring mechanism. MethodsThe method determines model update timing through a model prediction error monitoring mechanism and realizes the adaptive retraining update of the model based on voyage data by combining the sliding window technique and support vector machine. Taking a KCS container ship as the research object, the method is tested and validated under zigzag maneuvering and turning circle motion scenarios with variable speed, and the influence of the error monitoring mechanism’s hyperparameter selection on the online modeling is analyzed. ResultsThe simulation results show that the error detection mechanism can effectively reduce the frequency of online model updating and save computational resources. Compared with the offline method, this method can update the model in time when the dynamic characteristics of the ship change, thereby guaranteeing prediction accuracy. ConclusionThe proposed method is applicable to scenarios in which the dynamic characteristics of ships change due to their own attributes, environmental changes, etc. Thus, it has practical engineering significance by providing a technical method for the online modeling and prediction of ship motion. |
| format | Article |
| id | doaj-art-34ee640562ce4e178db7b2b63496f0ee |
| institution | OA Journals |
| issn | 1673-3185 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Editorial Office of Chinese Journal of Ship Research |
| record_format | Article |
| series | Zhongguo Jianchuan Yanjiu |
| spelling | doaj-art-34ee640562ce4e178db7b2b63496f0ee2025-08-20T02:00:51ZengEditorial Office of Chinese Journal of Ship ResearchZhongguo Jianchuan Yanjiu1673-31852025-02-01201586410.19693/j.issn.1673-3185.04019ZG4019Adaptive online modeling of ship maneuvering motion based on error monitoringYaohui YU0Suyang LIU1Zihao WANG2Wenbo XIE3Yan PENG4Institute of Artificial Intelligence, Shanghai University, Shanghai 200444, ChinaInstitute of Artificial Intelligence, Shanghai University, Shanghai 200444, ChinaInstitute of Artificial Intelligence, Shanghai University, Shanghai 200444, ChinaInstitute of Artificial Intelligence, Shanghai University, Shanghai 200444, ChinaInstitute of Artificial Intelligence, Shanghai University, Shanghai 200444, ChinaObjectiveAiming to address the problem of model inaccuracy caused by ship dynamic changes during actual navigation, this study proposes an adaptive online modeling method for ship maneuvering motion based on an error monitoring mechanism. MethodsThe method determines model update timing through a model prediction error monitoring mechanism and realizes the adaptive retraining update of the model based on voyage data by combining the sliding window technique and support vector machine. Taking a KCS container ship as the research object, the method is tested and validated under zigzag maneuvering and turning circle motion scenarios with variable speed, and the influence of the error monitoring mechanism’s hyperparameter selection on the online modeling is analyzed. ResultsThe simulation results show that the error detection mechanism can effectively reduce the frequency of online model updating and save computational resources. Compared with the offline method, this method can update the model in time when the dynamic characteristics of the ship change, thereby guaranteeing prediction accuracy. ConclusionThe proposed method is applicable to scenarios in which the dynamic characteristics of ships change due to their own attributes, environmental changes, etc. Thus, it has practical engineering significance by providing a technical method for the online modeling and prediction of ship motion.http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.04019shipsmaneuverabilityartificial intelligencemotion controlmotion predictiononline modelingsystem identificationtime-varying system |
| spellingShingle | Yaohui YU Suyang LIU Zihao WANG Wenbo XIE Yan PENG Adaptive online modeling of ship maneuvering motion based on error monitoring Zhongguo Jianchuan Yanjiu ships maneuverability artificial intelligence motion control motion prediction online modeling system identification time-varying system |
| title | Adaptive online modeling of ship maneuvering motion based on error monitoring |
| title_full | Adaptive online modeling of ship maneuvering motion based on error monitoring |
| title_fullStr | Adaptive online modeling of ship maneuvering motion based on error monitoring |
| title_full_unstemmed | Adaptive online modeling of ship maneuvering motion based on error monitoring |
| title_short | Adaptive online modeling of ship maneuvering motion based on error monitoring |
| title_sort | adaptive online modeling of ship maneuvering motion based on error monitoring |
| topic | ships maneuverability artificial intelligence motion control motion prediction online modeling system identification time-varying system |
| url | http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.04019 |
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