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Nonlinear model predictive position control for a tail-actuated robotic fish

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Abstract

Position control is a significant technique for the underwater application of robotic fish; however, it is also very challenging due to the underactuated property and input coupling of system dynamics. In this article, a two-stage orientation–velocity nonlinear model predictive controller is proposed to solve this problem. A scaled averaging model of tail-actuated robotic fish is constructed at first. Then, the novel strategy based on orientation and velocity control is developed as well as proved to be equivalent with position control in the sense of Lyapunov. Furthermore, a nonlinear model predictive controller with a two-stage switching strategy is designed to regulate the orientation and velocity error. Finally, the simulation results demonstrate the superiority of the proposed control algorithm compared with other methods. Particularly, there exists an interesting twist-braking behavior in simulation, which indicates that the proposed method makes better use of the system dynamics. The proposed method is efficient for not only bionic robotic fish but also other aquatic underactuated robots, which offers new insight into the position control of underwater robots.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant 61725305, Grant 61973303, Grant 61633020, Grant U1909206, and Grant 61421004, and in part by Key Research Program of Frontier Sciences, CAS, under Grant QYZDJ-SSW-JSC004.

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Authors and Affiliations

  1. State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Pengfei Zhang, Zhengxing Wu, Yan Meng, Min Tan & Junzhi Yu

  2. School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China

    Pengfei Zhang, Zhengxing Wu, Yan Meng & Min Tan

  3. State Key Laboratory for Turbulence and Complex Systems, Department of Mechanics and Engineering Science, BIC-ESAT, College of Engineering, Peking University, Beijing, 100871, China

    Junzhi Yu

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  1. Pengfei Zhang
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  2. Zhengxing Wu
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Correspondence to Junzhi Yu.

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Zhang, P., Wu, Z., Meng, Y. et al. Nonlinear model predictive position control for a tail-actuated robotic fish. Nonlinear Dyn 101, 2235–2247 (2020). https://doi.org/10.1007/s11071-020-05963-2

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  • DOI: https://doi.org/10.1007/s11071-020-05963-2

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