The vertical takeoff and landing (VTOL) aircraft has developed rapidly in recent years due to its excellent performance in terms of takeoff, landing and cruising. As a relatively complete concept of VTOL aircraft, the canard rotor/wing (CRW) aircraft has the advantages of high hovering efficiency and fast cruising speed. In this paper, the concept of reinforcement learning is introduced, and a neural network controller which does not distinguish the flight mode and does not depend on the model is designed. Firstly, the dynamic model of the studied CRW aircraft in transition flight mode is established. Then, a pitch angle neural network control strategy is designed for transition flight mode based on the deep deterministic policy gradient (DDPG) algorithm. Finally, the effectiveness of the proposed pitch angle control scheme based on reinforcement learning is verified by simulation tests.


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    Title :

    Flight Control of a Canard Rotor/Wing VTOL Aircraft Based on Reinforcement Learning Under Transition Flight Mode


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Fu, Wenxing (editor) / Gu, Mancang (editor) / Niu, Yifeng (editor) / Zhang, Yinong (author) / Zhao, Huimin (author) / Zhu, Dehai (author) / Wang, Ban (author) / Huang, Jiangtao (author) / Gao, Zhenghong (author)

    Conference:

    International Conference on Autonomous Unmanned Systems ; 2022 ; Xi'an, China September 23, 2022 - September 25, 2022



    Publication date :

    2023-03-10


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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