This paper investigates the optimal performance control problem for the trajectory tracking control for a stratospheric airship with external disturbance. A reinforcement learning adaptive tracking control for a stratospheric airship is proposed. First, according to the knowledge of dynamics and kinematics, we establish the model of a stratospheric airship used in this paper. Then, to solve external disturbance problem and enhance the system performance, a controller is proposed by means of a reinforcement learning (RL) method that is primarily based on two neural networks (NNs). In the last place, the stability analysis and numerical simulations are given to verify that the designed controller is effective.


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    Titel :

    Reinforcement Learning Adaptive Tracking Control for a Stratospheric Airship


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Jia, Yingmin (Herausgeber:in) / Zhang, Weicun (Herausgeber:in) / Fu, Yongling (Herausgeber:in) / Wang, Kang (Autor:in) / Liu, Yang (Autor:in) / Zheng, Zewei (Autor:in) / Zhu, Ming (Autor:in)

    Kongress:

    Chinese Intelligent Systems Conference ; 2020 ; Shenzhen City, China October 24, 2020 - October 25, 2020



    Erscheinungsdatum :

    24.09.2020


    Format / Umfang :

    14 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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