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A novel tracking control approach for unmanned underwater vehicles based on bio-inspired neurodynamics

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Abstract

A novel hybrid control approach is presented for trajectory tracking control of unmanned underwater vehicles in this paper. The kinematic and dynamic controllers are integrated by the proposed control strategy. The paper has two objectives. Firstly, an improved backstep method is proposed to generate the virtual velocity using a bio-inspired neurodynamics model in the kinematic controller. The bio-inspired neurodynamics model is intended to smooth the virtual velocity output to avoid speed jumps of the unmanned underwater vehicle caused by tracking errors and to meet the thruster control constraints. Secondly, a new sliding-mode method is added to the dynamic controller, which is robust against parameter inaccuracy and disturbances. The combined kinematic–dynamic control law is applied to the trajectory tracking problem of two different types of unmanned underwater vehicle. Finally, simulation results illustrate the performance of the proposed controller.

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Acknowledgments

This project is supported by the National Natural Science Foundation of China (51075257) and the Creative Activity Plan for Science and Technology Commission of Shanghai (10550502700), the Yangtze River Delta Region scientific and technological project (10595812700).

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Authors and Affiliations

  1. Laboratory of Underwater Vehicles and Intelligent Systems, Shanghai Maritime University, #1550 Haigang Avenue, Shanghai, 201306, People’s Republic of China

    Bing Sun & Daqi Zhu

  2. Control Science and Engineering Research Center, Jiangnan University, Wuxi, 214122, People’s Republic of China

    Feng Ding

  3. The Advanced Robotics and Intelligent Systems Laboratory, School of Engineering, University of Guelph, Guelph, ON, N1G2W1, Canada

    Simon X. Yang

Authors
  1. Bing Sun
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  2. Daqi Zhu
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  3. Feng Ding
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  4. Simon X. Yang
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Corresponding author

Correspondence to Daqi Zhu.

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Sun, B., Zhu, D., Ding, F. et al. A novel tracking control approach for unmanned underwater vehicles based on bio-inspired neurodynamics. J Mar Sci Technol 18, 63–74 (2013). https://doi.org/10.1007/s00773-012-0188-8

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  • DOI: https://doi.org/10.1007/s00773-012-0188-8

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