A LSSVR Interactive Network for AUV Motion Control
In view of the requirements on control precision of autonomous underwater vehicles (AUVs) in different operations, the improvement of AUV motion control accuracy is the focus of this paper. In regard to the unsatisfying robustness of traditional control methods, an interactive network based on Least...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/11/6/1111 |
| _version_ | 1827736882890407936 |
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| author | Chunmeng Jiang Lei Wan Hongrui Zhang Jian Tang Jianguo Wang Shupeng Li Long Chen Gongxing Wu Bin He |
| author_facet | Chunmeng Jiang Lei Wan Hongrui Zhang Jian Tang Jianguo Wang Shupeng Li Long Chen Gongxing Wu Bin He |
| author_sort | Chunmeng Jiang |
| collection | DOAJ |
| description | In view of the requirements on control precision of autonomous underwater vehicles (AUVs) in different operations, the improvement of AUV motion control accuracy is the focus of this paper. In regard to the unsatisfying robustness of traditional control methods, an interactive network based on Least Square Support Vector Regression (LSSVR) is therefore put forward. The network completed the identification of the strong nonlinear AUV dynamic characteristics based on the LSSVR theory and by virtue of the interactions between the offline and online modules, it achieved offline design and online optimization of the AUV control law. In addition to contrastive numerical simulations and sea trials with the classic S-plane method in AUV velocity and heading control, the LSSVR network was also tested in path following and long-range cruise. The precision and robustness and of the proposed network were verified by the high-accuracy control results of the aforesaid simulations and trials. The network can be of practical use in AUV control especially under unfamiliar water conditions with access to a limited number of control samples or little information of the operation site. |
| first_indexed | 2024-03-11T02:17:22Z |
| format | Article |
| id | doaj.art-664fc94fb16f452f863c818f09e76bd2 |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-11T02:17:22Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-664fc94fb16f452f863c818f09e76bd22023-11-18T11:06:03ZengMDPI AGJournal of Marine Science and Engineering2077-13122023-05-01116111110.3390/jmse11061111A LSSVR Interactive Network for AUV Motion ControlChunmeng Jiang0Lei Wan1Hongrui Zhang2Jian Tang3Jianguo Wang4Shupeng Li5Long Chen6Gongxing Wu7Bin He8Wuhan Institute of Shipbuilding Technology, Wuhan 430050, ChinaSchool of Naval Engineering, Harbin Engineering University, Harbin 150001, ChinaWuhan Institute of Shipbuilding Technology, Wuhan 430050, ChinaWuhan Institute of Shipbuilding Technology, Wuhan 430050, ChinaChina Ship Development and Design Center, Wuhan 430064, ChinaWuhan Institute of Shipbuilding Technology, Wuhan 430050, ChinaWuhan Institute of Shipbuilding Technology, Wuhan 430050, ChinaCollege of Ocean Science and Engineering, Shanghai Maritime University, Shanghai 201306, ChinaWuhan Second Ship Design and Research Institute, Wuhan 430205, ChinaIn view of the requirements on control precision of autonomous underwater vehicles (AUVs) in different operations, the improvement of AUV motion control accuracy is the focus of this paper. In regard to the unsatisfying robustness of traditional control methods, an interactive network based on Least Square Support Vector Regression (LSSVR) is therefore put forward. The network completed the identification of the strong nonlinear AUV dynamic characteristics based on the LSSVR theory and by virtue of the interactions between the offline and online modules, it achieved offline design and online optimization of the AUV control law. In addition to contrastive numerical simulations and sea trials with the classic S-plane method in AUV velocity and heading control, the LSSVR network was also tested in path following and long-range cruise. The precision and robustness and of the proposed network were verified by the high-accuracy control results of the aforesaid simulations and trials. The network can be of practical use in AUV control especially under unfamiliar water conditions with access to a limited number of control samples or little information of the operation site.https://www.mdpi.com/2077-1312/11/6/1111autonomous underwater vehiclemotion controlLSSVRinteractive networkcontroller design and optimization |
| spellingShingle | Chunmeng Jiang Lei Wan Hongrui Zhang Jian Tang Jianguo Wang Shupeng Li Long Chen Gongxing Wu Bin He A LSSVR Interactive Network for AUV Motion Control Journal of Marine Science and Engineering autonomous underwater vehicle motion control LSSVR interactive network controller design and optimization |
| title | A LSSVR Interactive Network for AUV Motion Control |
| title_full | A LSSVR Interactive Network for AUV Motion Control |
| title_fullStr | A LSSVR Interactive Network for AUV Motion Control |
| title_full_unstemmed | A LSSVR Interactive Network for AUV Motion Control |
| title_short | A LSSVR Interactive Network for AUV Motion Control |
| title_sort | lssvr interactive network for auv motion control |
| topic | autonomous underwater vehicle motion control LSSVR interactive network controller design and optimization |
| url | https://www.mdpi.com/2077-1312/11/6/1111 |
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