A neural dynamics model prediction-based adaptive control system for AUV formation control
ObjectivesThis paper seeks to provide a solution for the formation control issue that arises when autonomous underwater vehicles (AUVs) are subjected to interference from obstacles and complex ocean currents. Methods To tackle the issue of AUV hysteresis resulting from an overly rapid predicted conv...
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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.1673-3185.04045 |
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| author | Jiwen ZHANG Bo XU Chuyan WANG Zhaoyang WANG |
| author_facet | Jiwen ZHANG Bo XU Chuyan WANG Zhaoyang WANG |
| author_sort | Jiwen ZHANG |
| collection | DOAJ |
| description | ObjectivesThis paper seeks to provide a solution for the formation control issue that arises when autonomous underwater vehicles (AUVs) are subjected to interference from obstacles and complex ocean currents. Methods To tackle the issue of AUV hysteresis resulting from an overly rapid predicted convergence speed during dynamic obstacle avoidance, a multi-AUV formation adaptive control method (NDP-ABS) based on brain dynamics model prediction is created. Active and inhibitory sources are created to solve the local optimization problem of potential field methods. When paired with optimal control, dynamic obstacle avoidance, formation control, and predicted tracking are accomplished. Second, a nonlinear adaptive backstepping method is used to design the AUV expected tracking controller, which resolves the interference of shallow ocean current disturbances and nonlinear factors on the AUV expected tracking control in consideration of unknown nonlinear factors and ocean current disturbances introduced in the control law of the NDP process. Finally, Lyapunov theory is used to demonstrate the system's stability. ResultsThe anti-interference and obstacle avoidance performance of the NDP-ABS system are tested in six sets of comparative simulation tests, and the results confirm its efficacy. Conclusions The NDP-ABS formation scheme offers several benefits, including cheap obstacle avoidance costs, robust resistance to interference from ocean currents, high stability, and clear advantages in the non-explicit formation control of multiple AUVs. |
| format | Article |
| id | doaj-art-756a00bd14624b2c8d4f36a7779d82e5 |
| institution | DOAJ |
| 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-756a00bd14624b2c8d4f36a7779d82e52025-08-20T02:54:35ZengEditorial Office of Chinese Journal of Ship ResearchZhongguo Jianchuan Yanjiu1673-31852025-02-0120132633910.19693/j.issn.1673-3185.04045ZG4045A neural dynamics model prediction-based adaptive control system for AUV formation controlJiwen ZHANG0Bo XU1Chuyan WANG2Zhaoyang WANG3College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, ChinaCollege of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, ChinaCollege of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, ChinaCollege of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, ChinaObjectivesThis paper seeks to provide a solution for the formation control issue that arises when autonomous underwater vehicles (AUVs) are subjected to interference from obstacles and complex ocean currents. Methods To tackle the issue of AUV hysteresis resulting from an overly rapid predicted convergence speed during dynamic obstacle avoidance, a multi-AUV formation adaptive control method (NDP-ABS) based on brain dynamics model prediction is created. Active and inhibitory sources are created to solve the local optimization problem of potential field methods. When paired with optimal control, dynamic obstacle avoidance, formation control, and predicted tracking are accomplished. Second, a nonlinear adaptive backstepping method is used to design the AUV expected tracking controller, which resolves the interference of shallow ocean current disturbances and nonlinear factors on the AUV expected tracking control in consideration of unknown nonlinear factors and ocean current disturbances introduced in the control law of the NDP process. Finally, Lyapunov theory is used to demonstrate the system's stability. ResultsThe anti-interference and obstacle avoidance performance of the NDP-ABS system are tested in six sets of comparative simulation tests, and the results confirm its efficacy. Conclusions The NDP-ABS formation scheme offers several benefits, including cheap obstacle avoidance costs, robust resistance to interference from ocean currents, high stability, and clear advantages in the non-explicit formation control of multiple AUVs.http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.04045autonomous underwater vehiclesmotion controlformation controlbiological inspirationmodel predictionadaptive backstepping |
| spellingShingle | Jiwen ZHANG Bo XU Chuyan WANG Zhaoyang WANG A neural dynamics model prediction-based adaptive control system for AUV formation control Zhongguo Jianchuan Yanjiu autonomous underwater vehicles motion control formation control biological inspiration model prediction adaptive backstepping |
| title | A neural dynamics model prediction-based adaptive control system for AUV formation control |
| title_full | A neural dynamics model prediction-based adaptive control system for AUV formation control |
| title_fullStr | A neural dynamics model prediction-based adaptive control system for AUV formation control |
| title_full_unstemmed | A neural dynamics model prediction-based adaptive control system for AUV formation control |
| title_short | A neural dynamics model prediction-based adaptive control system for AUV formation control |
| title_sort | neural dynamics model prediction based adaptive control system for auv formation control |
| topic | autonomous underwater vehicles motion control formation control biological inspiration model prediction adaptive backstepping |
| url | http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.04045 |
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