To design a good control system for a 6 degree-of-freedom aircraft is not an easy work. The classic linear method such as PID can’t provide a good performance for complex nonlinear systems in some cases. In this paper, an end-to-end policy using Reinforcement Learning (RL) based on Proximal Policy Optimization (PPO) is proposed. This mothed is used to established a mapping from the observed states to the motor signals to control the attitude of quadrotor. In order to evaluate the performance of the end-to-end controller based on PPO, a RL-PID controller is designed to compare with the end-to-end controller in this paper. The result shows that the performance of the end-to-end controller based on PPO is better.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Attitude Control Based on Reinforcement Learning for Quadrotor


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Wu, Meiping (editor) / Niu, Yifeng (editor) / Gu, Mancang (editor) / Cheng, Jin (editor) / Wang, Yao (author) / Zhang, Weiping (author) / Mou, Jiawang (author) / Zheng, Kexin (author)

    Conference:

    International Conference on Autonomous Unmanned Systems ; 2021 ; Changsha, China September 24, 2021 - September 26, 2021



    Publication date :

    2022-03-18


    Size :

    8 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Attitude Control Based on Reinforcement Learning for Quadrotor

    Wang, Yao / Zhang, Weiping / Mou, Jiawang et al. | TIBKAT | 2022


    Attitude Control Based on Reinforcement Learning for Quadrotor

    Wang, Yao / Zhang, Weiping / Mou, Jiawang et al. | British Library Conference Proceedings | 2022



    Attitude control of a quadrotor

    Dikmen, I. Can / Arisoy, Aydemir / Temeltas, Hakan | IEEE | 2009


    Attitude control of a quadrotor

    Dikmen, I.C. / Arisoy, A. / Temeltas, H. | Tema Archive | 2009