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Volume 13
Issue 8
10.3390/act13080280
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Article

Simulation Training System for Parafoil Motion Controller Based on Actor–Critic RL Approach

by
Xi He
1,
Jingnan Liu
1,*,
Jing Zhao
1,
Ronghua Xu
2,
Qi Liu
2,
Jincheng Wan
2 and
Gang Yu
3
1
GNSS Research Center, Wuhan University, Wuhan 430072, China
2
Aviation Industry Corporation of China Aerospace Life Support Industries Ltd., Xiangyang 441003, China
3
School of Mechanical Engineering, Hubei University of Arts and Science, Xiangyang 441053, China
*
Author to whom correspondence should be addressed.
Actuators 2024, 13(8), 280; https://doi.org/10.3390/act13080280
Submission received: 19 June 2024 / Revised: 13 July 2024 / Accepted: 23 July 2024 / Published: 25 July 2024
(This article belongs to the Special Issue Advances in Dynamics and Motion Control of Unmanned Aerial/Underwater/Ground Vehicles)
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Abstract

The unique ram air aerodynamic shape and control rope pulling course of the parafoil system make it difficult to realize its precise control. At present, the commonly used control methods of the parafoil system include proportional–integral–derivative (PID) control, model predictive control, and adaptive control. The control precision of PID control and model predictive control is low, while the adaptive control has the problems of complexity and high cost. This study proposes a new method to improve the control precision of the parafoil system by establishing a parafoil motion simulation training system that trains the neural network controllers based on actor–critic reinforcement learning (RL). Simulation results verify the feasibility of the proposed parafoil motion-control-simulation training system. Furthermore, the test results of the real flight experiment based on the motion controller trained by the proximal policy optimization (PPO) algorithm are presented, which are close to the simulation results.
Keywords: parafoil system; precise control; motion controller; simulation training; actor–critic parafoil system; precise control; motion controller; simulation training; actor–critic

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MDPI and ACS Style

He, X.; Liu, J.; Zhao, J.; Xu, R.; Liu, Q.; Wan, J.; Yu, G. Simulation Training System for Parafoil Motion Controller Based on Actor–Critic RL Approach. Actuators 2024, 13, 280. https://doi.org/10.3390/act13080280

AMA Style

He X, Liu J, Zhao J, Xu R, Liu Q, Wan J, Yu G. Simulation Training System for Parafoil Motion Controller Based on Actor–Critic RL Approach. Actuators. 2024; 13(8):280. https://doi.org/10.3390/act13080280

Chicago/Turabian Style

He, Xi, Jingnan Liu, Jing Zhao, Ronghua Xu, Qi Liu, Jincheng Wan, and Gang Yu. 2024. "Simulation Training System for Parafoil Motion Controller Based on Actor–Critic RL Approach" Actuators 13, no. 8: 280. https://doi.org/10.3390/act13080280

APA Style

He, X., Liu, J., Zhao, J., Xu, R., Liu, Q., Wan, J., & Yu, G. (2024). Simulation Training System for Parafoil Motion Controller Based on Actor–Critic RL Approach. Actuators, 13(8), 280. https://doi.org/10.3390/act13080280

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