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A bioinspired neural dynamics-based approach to tracking control of autonomous surface vehicles subject to unknown ocean currents

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Abstract

This paper addresses the trajectory tracking control problem of an autonomous surface vehicle (ASV) subject to unknown ocean currents, where smooth and continuous velocity commands are desirable for safe and effective operation. A novel bioinspired approach is proposed by integrating three neural dynamics models into the conventional Lyapunov synthesis. The tracking controller is derived from the error dynamics analysis of the ASV and the stability analysis of the control system. A simple observer is proposed to estimate the unknown ocean currents, which only requires the position of the ASV. The overall control system under the controller and observer is rigorously proved to be asymptotically stable by a Lyapunov stability theory for cascaded systems. The most contribution is that the proposed tracking controller is capable of eliminating the sharp velocity jumps due to sudden tracking error changes and generating smooth and continuous control signals. In addition, it can deals with the situation with unknown ocean currents. The effectiveness and efficiency of the proposed approach are demonstrated through simulation and comparison studies.

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Acknowledgments

The authors would like to thank the anonymous reviewers for the valuable suggestions and comments. This work was supported in part by the National Science Foundation of China under Grants 61074112 and 61403135, the Scientific Research Fund of Hunan Provincial Education Department under Grant 14C0440, and Natural Sciences and Engineering Research Council (NSERC) Discovery Grant of Canada.

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Authors and Affiliations

  1. School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan, 411201, Hunan, China

    Changzhong Pan

  2. School of Automation, China University of Geosciences, Wuhan, 430074, Hubei, China

    Xuzhi Lai & Min Wu

  3. School of Engineering, University of Guelph, Guelph, N1G 2W1, ON, Canada

    Simon X. Yang

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  1. Changzhong Pan
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  2. Xuzhi Lai
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  3. Simon X. Yang
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  4. Min Wu
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Correspondence to Xuzhi Lai.

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Pan, C., Lai, X., Yang, S.X. et al. A bioinspired neural dynamics-based approach to tracking control of autonomous surface vehicles subject to unknown ocean currents. Neural Comput & Applic 26, 1929–1938 (2015). https://doi.org/10.1007/s00521-015-1839-6

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  • DOI: https://doi.org/10.1007/s00521-015-1839-6

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