The autonomous aerial refueling (AAR) has become an effective way to prolong air combat time in modern warfare. However, the control of the docking process should be precise enough because of the strong instability of the drogue. The bow wave is an important factor in disturbing the motion of drogue which is few mentioned in relevant research. A deep learning method is proposed to estimate the effect of the bow wave, which is hard to be predicted by accurate modeling. Considering the authenticity of model, the computational fluid dynamics (CFD) analysis is used to obtain the experiment data in the docking. Through the simulations and comparison, it is proved that the model fitted by deep learning is more accurate and the calculation speed is faster, which provides a feasible way for online optimization of AAR.


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    Titel :

    Deep Learning Based Bow Wave Modeling for UAV Aerial Refueling Docking


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Yan, Liang (Herausgeber:in) / Duan, Haibin (Herausgeber:in) / Yu, Xiang (Herausgeber:in) / Lun, Yuebin (Autor:in) / Wang, Honglun (Autor:in) / Liu, Yiheng (Autor:in)


    Erscheinungsdatum :

    2021-10-30


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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