Precise path following of underactuated ship based on neurodynamic optimization and model predictive control
ObjectiveThe traditional model predictive control method employs a repeated online optimization approach, resulting in a high computational burden for underactuated ship path-following predictive controller. To address this issue, this paper presents an efficient predictive controller for underactua...
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Editorial Office of Chinese Journal of Ship Research
2025-02-01
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| Series: | Zhongguo Jianchuan Yanjiu |
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| Online Access: | http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.04255 |
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| author | Junqiao SHI Cheng LIU Weili GUO Ting SUN Xuegang WANG Feng XU |
| author_facet | Junqiao SHI Cheng LIU Weili GUO Ting SUN Xuegang WANG Feng XU |
| author_sort | Junqiao SHI |
| collection | DOAJ |
| description | ObjectiveThe traditional model predictive control method employs a repeated online optimization approach, resulting in a high computational burden for underactuated ship path-following predictive controller. To address this issue, this paper presents an efficient predictive controller for underactuated ship path following based on the neurodynamic optimization system. Method First, the line-of-sight (LOS) guidance principle is employed to mitigate the underactuated problem herein; for kinematic model uncertainty in traditional LOS guidance law, a robust LOS guidance method based on the sliding mode concept is proposed. Furthermore, the sideslip angle induced by external disturbances negatively affects path following. To compensate for this effect, a robust adaptive LOS guidance method is proposed, enhancing robustness against model uncertainty and external disturbances. Second, in order to address the input saturation problem, the model predictive control is adopted herein to transform ship path following problem into the quadratic optimization problem with input constraints. Finally, the neurodynamic optimization solver is proposed based on the projection recurrent neural network herein to solve the quadratic optimization problem with input constraints, enhancing the computational efficiency.ResultsIn this study, both simulations for straight line path following and curved line path following are conducted. Overall, the simulation results show that the presented efficient predictive controller can achieve arbitrary path following. Additionally, the comparative simulations are performed, revealing that the presented method exhibits advantage in computational efficiency compared to the Fmincon optimization solver. Specifically, the neurodynamic optimization solver achieves approximately a 90-fold improvement in computational efficiency compared to the Fmincon optimization solver. ConclusionThe research results have practical value for improving the real-time performance of underactuated ship path following. In the future, the proposed real-time predictive control method will be extended to the application of multi-ship cooperative predictive control. |
| format | Article |
| id | doaj-art-374d293c7d064f00931faa01e6af3fc5 |
| 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-374d293c7d064f00931faa01e6af3fc52025-08-20T02:00:51ZengEditorial Office of Chinese Journal of Ship ResearchZhongguo Jianchuan Yanjiu1673-31852025-02-0120120321210.19693/j.issn.1673-3185.04255ZG4255Precise path following of underactuated ship based on neurodynamic optimization and model predictive controlJunqiao SHI0Cheng LIU1Weili GUO2Ting SUN3Xuegang WANG4Feng XU5Navigation College, Dalian Maritime University, Dalian 116026, ChinaNavigation College, Dalian Maritime University, Dalian 116026, ChinaNavigation College, Dalian Maritime University, Dalian 116026, ChinaNavigation College, Dalian Maritime University, Dalian 116026, ChinaCCCC Fourth Harbor Engineering Institute Co., Ltd, Guangzhou 510230, ChinaWuhan Second Ship Design and Research Institute, Wuhan 430205, ChinaObjectiveThe traditional model predictive control method employs a repeated online optimization approach, resulting in a high computational burden for underactuated ship path-following predictive controller. To address this issue, this paper presents an efficient predictive controller for underactuated ship path following based on the neurodynamic optimization system. Method First, the line-of-sight (LOS) guidance principle is employed to mitigate the underactuated problem herein; for kinematic model uncertainty in traditional LOS guidance law, a robust LOS guidance method based on the sliding mode concept is proposed. Furthermore, the sideslip angle induced by external disturbances negatively affects path following. To compensate for this effect, a robust adaptive LOS guidance method is proposed, enhancing robustness against model uncertainty and external disturbances. Second, in order to address the input saturation problem, the model predictive control is adopted herein to transform ship path following problem into the quadratic optimization problem with input constraints. Finally, the neurodynamic optimization solver is proposed based on the projection recurrent neural network herein to solve the quadratic optimization problem with input constraints, enhancing the computational efficiency.ResultsIn this study, both simulations for straight line path following and curved line path following are conducted. Overall, the simulation results show that the presented efficient predictive controller can achieve arbitrary path following. Additionally, the comparative simulations are performed, revealing that the presented method exhibits advantage in computational efficiency compared to the Fmincon optimization solver. Specifically, the neurodynamic optimization solver achieves approximately a 90-fold improvement in computational efficiency compared to the Fmincon optimization solver. ConclusionThe research results have practical value for improving the real-time performance of underactuated ship path following. In the future, the proposed real-time predictive control method will be extended to the application of multi-ship cooperative predictive control.http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.04255unmanned vehiclesmotion controlmodel predictive controlpath followingneurodynamic optimizationrobust adaptive line-of-sight guidancemaneuverability |
| spellingShingle | Junqiao SHI Cheng LIU Weili GUO Ting SUN Xuegang WANG Feng XU Precise path following of underactuated ship based on neurodynamic optimization and model predictive control Zhongguo Jianchuan Yanjiu unmanned vehicles motion control model predictive control path following neurodynamic optimization robust adaptive line-of-sight guidance maneuverability |
| title | Precise path following of underactuated ship based on neurodynamic optimization and model predictive control |
| title_full | Precise path following of underactuated ship based on neurodynamic optimization and model predictive control |
| title_fullStr | Precise path following of underactuated ship based on neurodynamic optimization and model predictive control |
| title_full_unstemmed | Precise path following of underactuated ship based on neurodynamic optimization and model predictive control |
| title_short | Precise path following of underactuated ship based on neurodynamic optimization and model predictive control |
| title_sort | precise path following of underactuated ship based on neurodynamic optimization and model predictive control |
| topic | unmanned vehicles motion control model predictive control path following neurodynamic optimization robust adaptive line-of-sight guidance maneuverability |
| url | http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.04255 |
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