Dynamic Docking Anti‐Disturbance Control of Overactuated AUV: System, Method, and Lake Trails
ABSTRACT Dynamic docking control technology is crucial for autonomous underwater vehicles (AUV) to perform tasks underwater. To enhance the docking success rate of AUVs during dynamic docking, this paper presents a robust anti‐disturbance control algorithm specifically designed for overactuated AUV...
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Published in | Journal of field robotics Vol. 42; no. 5; pp. 1617 - 1632 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
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Hoboken
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01.08.2025
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Online Access | Get full text |
ISSN | 1556-4959 1556-4967 |
DOI | 10.1002/rob.22444 |
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Abstract | ABSTRACT
Dynamic docking control technology is crucial for autonomous underwater vehicles (AUV) to perform tasks underwater. To enhance the docking success rate of AUVs during dynamic docking, this paper presents a robust anti‐disturbance control algorithm specifically designed for overactuated AUV dynamic docking scenarios. During a dynamic docking mission, the AUV's depth control is adversely affected by the complex flow field generated by the underwater recovery device. To address this issue, this research proposes an AUV control scheme that combines an extended state observer (ESO) with a combined disturbance rejection method of the elevator‐vertical tunnel controller. First, an ESO is constructed to estimate and compensate for complicated disturbances such as model uncertainty and environmental disturbances. These estimations are then incorporated into the control law to mitigate the effects of the complicated flow field interference experienced during the AUV's dynamic docking process. Second, as turbulence intensifies at the end of the docking stage, the vertical thrust allocation is achieved using a hyperbolic tangent transition function. This ensures the stability of the AUV's attitude and depth, thereby enabling precise docking. Finally, the effectiveness of the proposed control algorithm is verified through lake trials and compared against the classic proportional‐integral‐differential (PID) and active disturbance rejection control (ADRC) methods. The trial results indicate that the proposed control algorithm significantly reduces the pitch and depth errors of the AUV, resulting in a remarkable 91% success rate for dynamic docking (based on 45 tests). The lake trials demonstrate that the proposed control algorithm is highly precise and robust. |
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AbstractList | ABSTRACT
Dynamic docking control technology is crucial for autonomous underwater vehicles (AUV) to perform tasks underwater. To enhance the docking success rate of AUVs during dynamic docking, this paper presents a robust anti‐disturbance control algorithm specifically designed for overactuated AUV dynamic docking scenarios. During a dynamic docking mission, the AUV's depth control is adversely affected by the complex flow field generated by the underwater recovery device. To address this issue, this research proposes an AUV control scheme that combines an extended state observer (ESO) with a combined disturbance rejection method of the elevator‐vertical tunnel controller. First, an ESO is constructed to estimate and compensate for complicated disturbances such as model uncertainty and environmental disturbances. These estimations are then incorporated into the control law to mitigate the effects of the complicated flow field interference experienced during the AUV's dynamic docking process. Second, as turbulence intensifies at the end of the docking stage, the vertical thrust allocation is achieved using a hyperbolic tangent transition function. This ensures the stability of the AUV's attitude and depth, thereby enabling precise docking. Finally, the effectiveness of the proposed control algorithm is verified through lake trials and compared against the classic proportional‐integral‐differential (PID) and active disturbance rejection control (ADRC) methods. The trial results indicate that the proposed control algorithm significantly reduces the pitch and depth errors of the AUV, resulting in a remarkable 91% success rate for dynamic docking (based on 45 tests). The lake trials demonstrate that the proposed control algorithm is highly precise and robust. Dynamic docking control technology is crucial for autonomous underwater vehicles (AUV) to perform tasks underwater. To enhance the docking success rate of AUVs during dynamic docking, this paper presents a robust anti‐disturbance control algorithm specifically designed for overactuated AUV dynamic docking scenarios. During a dynamic docking mission, the AUV's depth control is adversely affected by the complex flow field generated by the underwater recovery device. To address this issue, this research proposes an AUV control scheme that combines an extended state observer (ESO) with a combined disturbance rejection method of the elevator‐vertical tunnel controller. First, an ESO is constructed to estimate and compensate for complicated disturbances such as model uncertainty and environmental disturbances. These estimations are then incorporated into the control law to mitigate the effects of the complicated flow field interference experienced during the AUV's dynamic docking process. Second, as turbulence intensifies at the end of the docking stage, the vertical thrust allocation is achieved using a hyperbolic tangent transition function. This ensures the stability of the AUV's attitude and depth, thereby enabling precise docking. Finally, the effectiveness of the proposed control algorithm is verified through lake trials and compared against the classic proportional‐integral‐differential (PID) and active disturbance rejection control (ADRC) methods. The trial results indicate that the proposed control algorithm significantly reduces the pitch and depth errors of the AUV, resulting in a remarkable 91% success rate for dynamic docking (based on 45 tests). The lake trials demonstrate that the proposed control algorithm is highly precise and robust. |
Author | Yang, Shaolong Xiang, Xianbo Liu, Yifan Guan, Xiawei Chen, Hong Duan, Yu |
Author_xml | – sequence: 1 givenname: Yu surname: Duan fullname: Duan, Yu organization: Huazhong University of Science and Technology – sequence: 2 givenname: Xiawei surname: Guan fullname: Guan, Xiawei organization: Wuhan Second Ship Design and Research Institute – sequence: 3 givenname: Yifan surname: Liu fullname: Liu, Yifan organization: Huazhong University of Science and Technology – sequence: 4 givenname: Shaolong surname: Yang fullname: Yang, Shaolong organization: Huazhong University of Science and Technology – sequence: 5 givenname: Xianbo orcidid: 0000-0002-6215-9864 surname: Xiang fullname: Xiang, Xianbo email: xbxiang@hust.edu.cn organization: Huazhong University of Science and Technology – sequence: 6 givenname: Hong surname: Chen fullname: Chen, Hong organization: Wuhan Second Ship Design and Research Institute |
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Dynamic docking control technology is crucial for autonomous underwater vehicles (AUV) to perform tasks underwater. To enhance the docking success... Dynamic docking control technology is crucial for autonomous underwater vehicles (AUV) to perform tasks underwater. To enhance the docking success rate of AUVs... |
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SubjectTerms | Algorithms autonomous underwater vehicle Autonomous underwater vehicles Control algorithms Control theory Disturbances dynamic docking Elevators (control surfaces) extended state observer Hyperbolic functions lake trail Rejection Robust control State observers |
Title | Dynamic Docking Anti‐Disturbance Control of Overactuated AUV: System, Method, and Lake Trails |
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