With the increasingly complex space combat, the cooperative operation of multiple vehicles will become the main form of the future world. However, there is not enough research on the cooperative control method of reentry vehicle, especially for high-speed reentry vehicle, its control accuracy and control time are not ideal, which cannot adapt to the needs of temporary formation transformation. To solve the above problems, this paper proposes a cooperative control method for reentry vehicles based on adaptive dynamic programming to achieve adaptive optimal formation control of multiple vehicles. To achieve fast convergence of an adaptive dynamic programming network, this paper proposes a quadratic critic network training method based on the optimal learning rate. To improve the control performance, under the leader-follower cooperative strategy, the flight trajectory of the leader aircraft is tracked by using the exact optimality of adaptive dynamic programming. To meet the requirements of a variety of formation transformations, the network parameters are evaluated by offline training, and the neural network fitting method is used to realize the online cooperative control of multiple vehicles under different flight conditions. Finally, simulation verifies the performance of formation control and the adaptability of formation transformation for the proposed approach.


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    Titel :

    Reentry Vehicle Formation Control Method Based on Adaptive Dynamic Programming


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Wang, Qing (Herausgeber:in) / Dong, Xiwang (Herausgeber:in) / Song, Peng (Herausgeber:in) / Sun, Zhengxiang (Autor:in) / Jia, Pinghui (Autor:in) / Li, Wei (Autor:in) / Wang, Yudong (Autor:in) / Yan, Chuxiong (Autor:in)

    Kongress:

    Chinese Conference on Swarm Intelligence and Cooperative Control ; 2023 ; Nanjing, China November 24, 2023 - November 27, 2023



    Erscheinungsdatum :

    15.06.2024


    Format / Umfang :

    17 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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