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Research on Autonomous Landing Control of Carrier-borne UCAV Based on Deep Reinforcement Learning Technology(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2022年03期
Page:
63-71
Research Field:
计算机科学与技术
Publishing date:

Info

Title:
Research on Autonomous Landing Control of Carrier-borne UCAV Based on Deep Reinforcement Learning Technology
Author(s):
Huang Jiangtao; Liu Gang; Zhou Pan; Zhang Sheng; Du Xin
(Aerospace Technology Institute,China Aerodynamics Research and Development Center,Mianyang 621000,China)
Keywords:
reinforcement learning; carrier-borne UAV; intelligent carrier landing; control surface command; deep neural network
PACS:
V211.3
DOI:
10.3969/j.issn.1672-1292.2022.03.009
Abstract:
Autonomous landing is an important problem and a key technology for future Carrier-borne UAV. Based on the TD3 algorithm,combined with the 6-DOF motion model of carrier aircraft and the motion model of aircraft carrier,an interactive deep reinforcement learning simulation environment is constructed. In the process of simulation training,the corresponding simplified motion model is established by considering the sea conditions,three line disturbances of aircraft carrier including surge,sway and heave,and three angular disturbances of roll,pitch and yaw. Based on the aerodynamic data of a certain type of aircraft,the aerodynamic model is established,and the six degree of freedom dynamics model is also established. Based on TD3 reinforcement learning algorithm,this paper further introduces an auxiliary network,an adaptive variance and learning step adjustment algorithm to accelerate convergence and improve training stability. Furthermore,combined with feed forward deep neural network technology,an interactive training environment for carrier based aircraft landing is established on high performance GPU workstation. Through the "trial and error" training of a certain type of Carrier-borne UAV in interactive environment,the feasibility of AI technology in Carrier-borne UAV autonomous landing control is verified.

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Last Update: 2022-09-15