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Volume 27 Issue 6
 
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Article Navigation >  Journal of Unmanned Undersea Systems  > 2019  >  27(6): 704-710
ZHU Hong-xiu, DU Chuang, CHU Yan-bin, ZHENG Quan, LIU Zhao-ying, DING Hao-nan. Obstacles Avoiding Method for Electromagnetic Actuated Robotic Fish[J]. Journal of Unmanned Undersea Systems, 2019, 27(6): 704-710. doi: 10.11993/j.issn.2096-3920.2019.06.015
Citation: ZHU Hong-xiu, DU Chuang, CHU Yan-bin, ZHENG Quan, LIU Zhao-ying, DING Hao-nan. Obstacles Avoiding Method for Electromagnetic Actuated Robotic Fish[J]. Journal of Unmanned Undersea Systems, 2019, 27(6): 704-710. doi: 10.11993/j.issn.2096-3920.2019.06.015
shu

Obstacles Avoiding Method for Electromagnetic Actuated Robotic Fish

doi: 10.11993/j.issn.2096-3920.2019.06.015

  • School of Electrical and Information Engineering, China University of Mining and TechnologyBeijing, Beijing 100083, China

  • Received Date: 2019-04-14
  • Rev Recd Date: 2019-05-19
  • Publish Date: 2019-12-31
    Abstract
  • A fuzzy obstacle avoidance control method for the robotic fish actuated by electromagnetic actuator was proposed. And the software FLUENT was employed to perform turning simulation by using its user define function(UDF) and the dynamic mesh technology. Infrared distance sensor was used. The input and output membership functions of the fuzzy controller were set in Matlab, and the rules of fuzzy control were summarized. Furthermore, an experimental platform was built to conduct underwater turning for obstacle avoidance experiment of the robotic fish. Experimental results show that the fuzzy control combined with infrared distance sensor can realize obstacle avoidance effectively when the elec-tromagnetic actuated robot fish swims in a two-dimensional plane.

     

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    • References(15)
  • [1]
    Shang L, Wang S, Tan M, et al. Motion Control for an Underwater Robotic Fish with Two Undulating Long-fins [C]//Proceedings of the 48th IEEE Conference on Decision and Control (CDC) Held Jointly with 2009 28th Chi- nese Control Conference. Shanghai, China: IEEE, 2009.
    [2]
    钟宏伟. 国外无人水下航行器装备与技术现状及展望[J]. 水下无人系统学报, 2017, 25(4): 215-225.

    Zhong Hong-wei. Review and Prospect of Equipment and Techniques for Unmanned Undersea Vehicle in Foreign Countries[J]. Journal of Unmanned Undersea Systems, 2017, 25(4): 215-225.
    [3]
    Phuc N D, Truongthinh N. A Solution of Obstacle Collision Avoidance for Robotic Fish Based on Fuzzy Systems[C]//IEEE International Conference on Robotics & Biomimetics. Phuket, Thailand: IEEE, 2012.
    [4]
    Lee P J, Wang W J. Robotic Fish Kinectics Design Based on a Fuzzy Control[M]//Latest Advances in Robot Kinematics. Springer: Dordrecht, 2012: 67-74.
    [5]
    Zhang Q, Chen D, Chen T. An Obstacle Avoidance Method of Soccer Robot Based on Evolutionary Artificial Potential Field[J]. Energy Procedia, 2012, 16(5): 1792-1798.
    [6]
    金久才. 无人水下自主航行器(AUV)避碰研究[D]. 呼和浩特: 内蒙古大学, 2008.
    [7]
    Huang Z, Zhu D, Bing S. A Multi-AUV Cooperative Hunting Method in 3-D Underwater Environment with Obstacle[J]. Engineering Applications of Artificial Intelligence, 2016, 50: 192-200.
    [8]
    Braginsky B, Guterman H. Obstacle Avoidance Approaches for Autonomous Underwater Vehicle: Simulation and Experimental Results[J]. IEEE Journal of Oceanic Engineering, 2016, 41(4): 882-892.
    [9]
    Sepulveda C A, Donley J M, Konstantinidis P, et al. Convergent Evolution in Mechanical Design of Lamnid Sha- rks and Tunas[J]. Nature, 2004, 429(6987): 61-65.
    [10]
    Stavridis S, Papageorgiou D, Doulgeri Z. Dynamical System Based Robotic Motion Generation with Obstacle Avoidance[J]. IEEE Robotics and Automation Letters, 2017, 2(2): 712-718.
    [11]
    Guan Z, Nong G, Gao W, et al. 3D Hydrodynamic Analysis of a Biomimetic Robot Fish[C]//International Conference on Control Automation Robotics & Vision. Singapore: IEEE, 2011.
    [12]
    Zhao Z Y, Hong Z H, Deng Y S. Angle Measurement of Robotic Fish Based on Kalman Filter[J]. Applied Mechanics & Materials, 2014, 568-570: 1049-1053.
    [13]
    Xia X, Li T. A Fuzzy Control Model Based on BP Neural Network Arithmetic for Optimal Control of Smart City Facilities[J]. Personal and Ubiquitous Computing, 2019, 23(3-4): 453-463.
    [14]
    Vafamand N, Khooban M H, Dragicevic T, et al. Robust Non-fragile Fuzzy Control of Uncertain DC Microgrids Feeding Constant Power Loads[J]. IEEE Transactions on Power Electronics, 2019, 34(11): 11300-11308.
    [15]
    Liu W, Xin Z, Chen Z. Fuzzy Rule Optimization and Reduction Based on Recursive Neural Networks[C]// International Conference on Control & Automation. Xiamen, China: IEEE, 2019.
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