The purpose of this paper is to study the control method of the Robotic Manta and complete its depth control using a T-S fuzzy neural network controller.

    Methods

    The Robotic Manta adopts Median and/or Paired Fin propulsion mode, which has good stability. By adjusting the caudal fin angle, the Robotic Manta can swim upward or downward. Due to the complex hydrodynamics and the uncertainty existing in the environment, it is difficult to establish an accurate mathematical model. In this paper, data acquisition is carried out for the depth control of the Robotic Manta and a T-S fuzzy neural network is designed and trained. Finally, this paper implements the automatic depth control of the Robotic Manta with the T-S fuzzy neural network controller.

    Findings

    The experimental results show that the depth error of the Robotic Manta is less than 60 mm, with good rapidity and small overshoot, which verifies the effectiveness of the T-S fuzzy neural network controller in design and implementation.


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    Title :

    Control of Robotic Manta Based on T-S Fuzzy Neural Network


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Wu, Meiping (editor) / Niu, Yifeng (editor) / Gu, Mancang (editor) / Cheng, Jin (editor) / Cao, Yonghui (author) / Xie, Yu (author) / Ma, Shumin (author) / Zhang, Daili (author) / Hao, Yiwei (author) / He, Yue (author) ... [more]

    Conference:

    International Conference on Autonomous Unmanned Systems ; 2021 ; Changsha, China September 24, 2021 - September 26, 2021



    Publication date :

    2022-03-18


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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