基于神经网络和干扰观测器的UAV自动着舰控制

doi:10.7527/S1000-6893.2022.26963

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基于神经网络和干扰观测器的UAV自动着舰控制

胡伟¹, 万文章², 陈谋¹

1. 南京航空航天大学自动化学院，南京 210016;
2. 航空工业沈阳飞机设计研究所，沈阳 110035

收稿日期:2022-01-18 修回日期:2022-01-28 发布日期:2022-03-04
通讯作者: 陈谋,E-mail:chenmou@nuaa.edu.cn E-mail:chenmou@nuaa.edu.cn
基金资助:
江苏省重点研发计划（社会发展）（BE2020704）；航空科学基金（20200007052001）

Neural network and disturbance observer based control for automatic carrier landing of UAV

HU Wei¹, WAN Wenzhang², CHEN Mou¹

1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
2. AVIC Shenyang Aircraft Design and Research Institute, Shenyang 110035, China

Received:2022-01-18 Revised:2022-01-28 Published:2022-03-04
Supported by:
Key Research and Development Projects （Social Development） in Jiangsu Province of China （BE2020704）； Aeronautical Science Foundation of China （20200007052001）

摘要/Abstract

摘要： 针对干扰下的舰载无人机（UAV）自动着舰问题，提出了一种融合神经网络与干扰观测器的自动着舰控制方法。首先采用神经网络处理系统不确定引入干扰观测器逼近系统外部干扰，同时基于神经网络输出和干扰观测器输出设计了非线性自动着舰控制器，实现了对着舰指令的有效跟踪。然后利用李雅普诺夫稳定性方法严格证明了所有闭环系统信号的收敛性，保证了舰载UAV自动精确着舰控制。最后进行数字仿真验证，仿真结果表明设计的基于神经网络和干扰观测器的自动着舰控制方法是有效的。

关键词: 舰载无人机, 飞行控制, 自动着舰控制, 神经网络, 干扰观测器

Abstract: An automatic carrier landing control method based on the neural network and disturbance observer is proposed for the Unmanned Aerial Vehicle （UAV） with dynamic disturbance. The neural network is employed to deal with system uncertainty， and the disturbance observer is employed to estimate the external disturbance of the UAV. By using the neural network output and disturbance observer output， a nonlinear automatic carrier landing controller for the UAV is designed to realize effective tracking of the landing control command. Utilizing the Lyapunov stability method， the convergence of all the closed-loop signals is proved strictly， ensuring the precise automatic carrier landing control of the UAV. Simulation results show the effectiveness of the proposed control method.

Key words: shipboard unmanned aerial vehicle, flight control, automatic carrier landing control, neural network, disturbance observer

中图分类号:

V249

胡伟, 万文章, 陈谋. 基于神经网络和干扰观测器的UAV自动着舰控制[J]. 航空学报, 2022, 43(S1): 726963-726963.

HU Wei, WAN Wenzhang, CHEN Mou. Neural network and disturbance observer based control for automatic carrier landing of UAV[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(S1): 726963-726963.

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E-mail：hkxb@buaa.edu.cn

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

基于神经网络和干扰观测器的UAV自动着舰控制

Neural network and disturbance observer based control for automatic carrier landing of UAV

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