Meta-aircraft, in High-Altitude, Long-Endurance (HALE) unmanned aerial vehicle (UAV) applications, utilize a strategy of formation flying in the stratosphere and aerial docking in the troposphere to enhance flight range and gust resistance. This paper explores an aerial docking strategy for unmanned meta-aircraft using a surrogate model based on aerodynamic data. The study begins with an analysis of the aerodynamic characteristics and the establishment of a dynamic model, followed by the development of a surrogate model using the vortex lattice method and a BP neural network. This model accurately simulates aerodynamic changes near the wingtip. Optimization of the docking process, focusing on impulse and moment of impulse, is achieved using a greedy algorithm. The results show a reduction in drag impulse and rolling moment by 10.89% and 15.76%, respectively, thereby easing the burden on the control system of UAVs.


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    Title :

    Research on an Aerial Docking Strategy for Meta-UAVs Using Aerodynamic Data Surrogate Models


    Contributors:
    Kangwen Sun (author) / Yixiang Gao (author) / Zhiyao Wang (author) / Haoquan Liang (author) / Chenxuan Zhao (author) / Xinzhe Ji (author)


    Publication date :

    2024




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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