This paper presents an intelligent morphing decision method, utilizing neural networks, designed to address the successive autonomic decision challenge faced by hypersonic morphing flight vehicles (HMFV). Initially, a dynamic model of a HMFV with a successive adjustable sweep angle is developed. Then, considering the external disturbance and the heat flux density constraint of the flight process, by segmenting the reference track and add interference, a trajectory sample set is generated by the Legendre pseudo-spectral method. The neural network is trained to automatically adjust the sweep angle during the gliding phase by analyzing the flight state, making intelligent decisions. Finally, the developed intelligent decision-making algorithm is utilized for trajectory optimization. The simulation results demonstrate a significant enhancement in the distance achieved through intelligent decision morphing compared to program-based morphing. The trajectory can be adjusted to enhance the range based on the intelligent decision-making sweep angle of the current flight state.


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    Titel :

    Hypersonic Vehicle Morphing Decision Founded on Neural Network


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Yan, Liang (Herausgeber:in) / Duan, Haibin (Herausgeber:in) / Deng, Yimin (Herausgeber:in) / Hou, Linfei (Autor:in) / Liu, Hao (Autor:in) / Jin, Huanying (Autor:in) / Wang, Rui (Autor:in)

    Kongress:

    International Conference on Guidance, Navigation and Control ; 2024 ; Changsha, China August 09, 2024 - August 11, 2024



    Erscheinungsdatum :

    07.03.2025


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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