Deep-Reinforcement-Learning-Based Active Disturbance Rejection Control for Lateral Path Following of Parafoil System

Yuemin Zheng, Jin Tao (), Qinglin Sun, Hao Sun, Zengqiang Chen, Mingwei Sun and Feng Duan ()
Additional contact information
Yuemin Zheng: College of Artificial Intelligence, Nankai University, Tianjin 300350, China
Jin Tao: College of Artificial Intelligence, Nankai University, Tianjin 300350, China
Qinglin Sun: College of Artificial Intelligence, Nankai University, Tianjin 300350, China
Hao Sun: College of Artificial Intelligence, Nankai University, Tianjin 300350, China
Zengqiang Chen: College of Artificial Intelligence, Nankai University, Tianjin 300350, China
Mingwei Sun: College of Artificial Intelligence, Nankai University, Tianjin 300350, China
Feng Duan: College of Artificial Intelligence, Nankai University, Tianjin 300350, China

Sustainability, 2022, vol. 15, issue 1, 1-18

Abstract: The path-following control of the parafoil system is essential for executing missions, such as accurate homing and delivery. In this paper, the lateral path-following control of the parafoil system is studied. First, considering the relative motion between the parafoil canopy and the payload, an eight-degree-of-freedom (DOF) model of the parafoil system is constructed. Then, a guidance law containing the position deviation and heading angle deviation is proposed. Moreover, a linear active disturbance rejection controller (LADRC) is designed based on the guidance law to allow the parafoil system to track the desired path under internal unmodeled dynamics or external environmental disturbances. For the adaptive tuning of the controller parameters, a deep Q-network (DQN) is applied to the LADRC-based path-following control system, and the controller parameters can be adjusted in real time according to the system’s states. Finally, the effectiveness of the proposed method is applied to a parafoil system following circular and straight paths in an environment with wind disturbances. The simulation results show that the proposed method is an effective means to realize the lateral path-following control of the parafoil system, and it can also promote the development of intelligent controllers.

Keywords: path-following control; parafoil system; linear active disturbance rejection control; deep Q-network; parameter optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/1/435/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/1/435/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2022:i:1:p:435-:d:1016532

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().