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Tracking control of an underwater manipulator using active disturbance rejection

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Abstract

An active disturbance rejection controller for a 2-DOF underwater manipulator is proposed in this study. The manipulator system has the characteristics of non-linearity, strong coupling and uncertainties within its model. Its operation is often disturbed by unknown water currents, so the anti-disturbance control of underwater manipulators has always been a challenge. The proposed controller in this study basically does not rely on the precise mathematical model of the object, and the model even can be decoupled. This method can eliminate the influence of model errors, time-varying parameters and external interference on the control effect. First, the entire manipulator treats different joints as several subsystems. For each joint subsystem, hydrodynamic forces, coupling terms between joints and unknown environmental disturbances are regarded as total disturbances. Subsequently, an extended state observer was designed to estimate and compensate for the total interference. In order to improve the disturbance observation effect of the extended state observer, the inertia matrix of the system is used to decouple the static part. Finally, the effectiveness of the proposed method is verified by both simulation and experiments. From the comparisons, it is confirmed that the quality of our controller in the presence of a certain inertial matrix error is better than traditional PD and continuous sliding mode control in terms of accuracy, dynamic characteristics as well as robustness.

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Funding

This work is supported by the project of National Natural Science Foundation of China (No. 62373285), the Innovative Projects (No. 2021-XXXX-LB-010-11), the Shanghai 2021 “Science and Technology Innovation Action Plan” with Special Project of Biomedical Science and Technology Support (No. 21S31902800), and the Key Pre-Research Project of the 14th-Five-Year-Plan on Common Technology. Meanwhile, this work is also partially supported by the Fundamental Research Funds for the Central Universities and the “National High Level Overseas Talent Plan” project, the “National Major Talent Plan” project (No. 2022-XXXX-XXX-079), as well as one key project (No. XM2023CX4013). It is also partially sponsored by the fundamental research project (No. XXXX2022YYYC133), the Shanghai Industrial Collaborative Innovation Project (Industrial Development Category, No. HCXBCY-2022-051), Laboratory fund of Wuhan Digital Engineering Institute of CSSC, the project of Shanghai Key Laboratory of Spacecraft Mechanism (No. 18DZ2272200), as well as the project of Space Structure and Mechanism Technology Laboratory of China Aerospace Science and Technology Group Co. Ltd (No. YY-F805202210015). All these supports are highly appreciated.

Author information

Authors and Affiliations

  1. Laboratory of Robotics and Multibody System, Tongji University, Shanghai, 201804, China

    Qirong Tang, Daopeng Jin, Jiang Li & Minghao Liu

  2. Naval Research Academy, Beijing, 102442, China

    Rong Luo

  3. Naval Research Institute, Shanghai, 200235, People’s Republic of China

    Rui Tao & Chonglun Li

  4. Naval Medical Center, Shanghai, 200433, People’s Republic of China

    Chuan Wang

Authors
  1. Qirong Tang
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  2. Daopeng Jin
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  3. Rong Luo
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  4. Rui Tao
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  5. Chonglun Li
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  6. Jiang Li
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  7. Minghao Liu
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  8. Chuan Wang
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Contributions

All the authors have contributed to the concept and design of the research. Qirong Tang proposed the investigation originally and organized the work from the beginning to the end, while he also wrote and revised the texts with several rounds. Daopeng Jin developed the trajectory tracking control algorithm, implemented the source code, and prepared manuscript materials. During the research, Jiang Li and Minghao Liu built experimental framework, and executed the experiments. Rong Luo, Rui Tao, Chonglun Li, and Chuan Wang prepared simulation studies and data analysis, provided experiment occasions. The final manuscript was revised and approved by all authors.

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Correspondence to Qirong Tang.

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Tang, Q., Jin, D., Luo, R. et al. Tracking control of an underwater manipulator using active disturbance rejection. J Mar Sci Technol 28, 770–783 (2023). https://doi.org/10.1007/s00773-023-00956-3

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  • DOI: https://doi.org/10.1007/s00773-023-00956-3

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