Optimal tracking controllers with Off-policy Reinforcement Learning Algorithm in Quadrotor

• Autorzy: Pham Dinh Duong , Cao Thanh Trung , Nguyen Tat Chung , Dao Phuong Nam

Identyfikatory

DOI

10.15439/2022R52

• Języki publikacji: EN

Abstrakty

EN

In this study, the optimal tracking control problem for the quadrotor which is a highly coupling system with completely unknown dynamics is addressed based on data by introducing the reinforcement learning (RL) technique. The proposed Off-policy RL algorithm does not need any knowledge of quadrotor model. By collecting data, which is the states of quadrotor system then using an actor-critic networks (NNs) to solve the optimal tracking trajectory problem. Finally, simulation results are provided to illustrate the effectiveness of proposed method.

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2022
• Tom: Vol. 33
• Strony: 29--32
• Opis fizyczny: Bibliogr. 9 poz., rys., wykr.

Twórcy

autor

Pham Dinh Duong

autor

Cao Thanh Trung

• Master, PhD Scholarship Programme of Vingroup Innovation Foundation (VINIF), Institute of Big Data

autor

Nguyen Tat Chung

autor

Dao Phuong Nam

Bibliografia

• 1. E. Altug, J. Ostrowski, and R. Mahony. Control of a quadrotor helicopter using visual feedback. In Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), volume 1, pages 72–77 vol.1, 2002.
• 2. A. Das, F. Lewis, and K. Subbarao. Backstepping approach for controlling a quadrotor using lagrange form dynamics. Journal of Intelligent and Robotic Systems, 56:127–151, 09 2009.
• 3. Y. Li and S. Song. A survey of control algorithms for quadrotor unmanned helicopter. In 2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI), pages 365–369, 2012.
• 4. C. Mu, C. Sun, and W. Xu. Fast sliding mode control on air-breathing hypersonic vehicles with transient response analysis. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 230, 11 2015.
• 5. A. Tayebi and S. McGilvray. Attitude stabilization of a vtol quadrotor aircraft. IEEE Transactions on Control Systems Technology, 14(3):562–571, 2006.
• 6. A. Tayebi and S. McGilvray. Attitude stabilization of a vtol quadrotor aircraft. IEEE Transactions on Control Systems Technology, 14(3):562–571, 2006.
• 7. W. Wang, H. Ma, and C.-Y. Sun. Control system design for multi-rotor mav. Journal of Theoretical and Applied Mechanics, 51:1027–1038, 01 2013.
• 8. G. Xiao, H. Zhang, Y. Luo, and H. Jiang. Data-driven optimal tracking control for a class of affine non-linear continuous-time systems with completely unknown dynamics. Iet Control Theory and Applications, 10:700–710, 2016.
• 9. W. Zhao, H. Liu, F. L. Lewis, and X. Wang. Data-driven optimal formation control for quadrotor team with unknown dynamics. IEEE Transactions on Cybernetics, pages 1–10, 2021.

Uwagi

PL

Opracowane ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)