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

HU Wei; WAN Wenzhang; CHEN Mou

doi:10.7527/S1000-6893.2022.26963

ACTA AERONAUTICAET ASTRONAUTICA SINICA >

2022 , Vol. 43 >Issue S1: 726963 - 726963

DOI: https://doi.org/10.7527/S1000-6893.2022.26963

Swarm Intelligence and Cooperative Control

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

HU Wei ,
WAN Wenzhang ,
CHEN Mou

Expand

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 date: 2022-01-18

Revised date: 2022-01-28

Online 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）

Fold

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

Cite this article

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 . DOI: 10.7527/S1000-6893.2022.26963

References

[1] LIANG L, XIAO J, DENG Y C. Research and development trend of carrier landing technology of UAV[J]. Journal of Xi'an Aeronautical University, 2020, 38(5): 23-28 (in Chinese). 梁磊, 肖静, 邓扬晨. 舰载无人机着舰技术现状及发展趋势[J]. 西安航空学院学报, 2020, 38(5): 23-28.
[2] YU L, ZHANG J B, XU L W. Research and development trend of foreign military UAV[J]. Aerodynamic Missile Journal, 2020(6): 46-49 (in Chinese). 于力, 张金榜, 徐磊武. 外军舰载无人机应用现状及发展趋势[J]. 飞航导弹, 2020(6): 46-49.
[3] WU W H, ZHANG Y, HU Y N, et al. Research development in nonlinear backstepping control method of carrier-based aircraft landing[J]. Systems Engineering and Electronics, 2018, 40(7): 1578-1587 (in Chinese). 吴文海, 张杨, 胡云安, 等. 舰载机着舰非线性反演控制方法研究进展[J]. 系统工程与电子技术, 2018, 40(7): 1578-1587.
[4] LIANG T J, CHEN X M, YANG Z X, et al. Trajectory control method for unmanned carrier aircraft taxiing[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(2): 289-296 (in Chinese). 梁天骄, 陈晓明, 杨朝旭, 等. 舰载无人机滑行轨迹控制方法[J]. 北京航空航天大学学报, 2021, 47(2): 289-296.
[5] ZHU J F, HUANG Y P. Research on longitudinal control system of unmanned aerial vehicle landing[J]. Ship Science and Technology, 2019, 41(12): 217-219 (in Chinese). 朱剑芳, 黄运平. 无人机着舰纵向控制系统研究[J]. 舰船科学技术, 2019, 41(12): 217-219.
[6] YANG L Q, ZHEN Z Y, XING D J, et al. Automatic carrier landing adaptive control system design of carrier-based UAV[J]. Flight Dynamics, 2018, 36(6): 36-39 (in Chinese). 杨柳青, 甄子洋, 邢冬静, 等. 舰载无人机自动着舰自适应控制系统设计[J]. 飞行力学, 2018, 36(6): 36-39.
[7] RUBIO HERVAS J, REYHANOGLU M, TANG H, et al. Nonlinear control of fixed-wing UAVs in presence of stochastic winds[J]. Communications in Nonlinear Science and Numerical Simulation, 2016, 33: 57-69.
[8] CHAKRABORTY A, SEILER P, BALAS G J. Susceptibility of F/A-18 flight controllers to the falling-leaf mode: linear analysis[J]. Journal of Guidance, Control, and Dynamics, 2011, 34(1): 57-72.
[9] ZHANG Y, WU W H, HU Y N, et al. Design of landing trajectory tracking robust controller for carrier-based unmanned aerial vehicle[J]. Control Theory & Applications, 2018, 35(4): 557-565 (in Chinese). 张杨, 吴文海, 胡云安, 等. 舰载无人机着舰轨迹跟踪鲁棒控制器设计[J]. 控制理论与应用, 2018, 35(4): 557-565.
[10] LIU C, LU L B, MIAO Y H, et al. Dynamic inversion control for fixed-wing UAVs based on sliding mode extended disturbance observer[J]. Electronics Optics & Control, 2018, 25(8): 32-38, 64 (in Chinese). 刘畅, 芦利斌, 苗育红, 等. 基于滑模扩张干扰观测器的固定翼无人机动态逆控制[J]. 电光与控制, 2018, 25(8): 32-38, 64.
[11] LEE S, LEE J, LEE S, et al. Sliding mode guidance and control for UAV carrier landing[J]. IEEE Transactions on Aerospace and Electronic Systems, 2019, 55(2): 951-966.
[12] WANG L P, ZHANG Z, ZHU Q D, et al. Longitudinal automatic carrier landing system guidance law using model predictive control with an additional landing risk term[J]. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2019, 233(3): 1089-1105.
[13] ZHENG F Y, ZHEN Z Y, GONG H J. Observer-based backstepping longitudinal control for carrier-based UAV with actuator faults[J]. Journal of Systems Engineering and Electronics, 2017, 28(2): 322-377.
[14] SUN Y, ZHANG W G, ZHANG M. Backstepping adaptive high maneuvers flight control based on neural network[J]. Systems Engineering and Electronics, 2011, 33(5): 1113-1117 (in Chinese). 孙勇, 章卫国, 章萌. 基于神经网络的反步自适应大机动飞行控制[J]. 系统工程与电子技术, 2011, 33(5): 1113-1117.
[15] CHEN M, GE S S, HOW B V E. Robust adaptive neural network control for a class of uncertain MIMO nonlinear systems with input nonlinearities[J]. IEEE Transactions on Neural Networks, 2010, 21(5): 796-812.
[16] CHEN M, ZOU Q Y, JIANG C S, et al. Dynamical inversion flight control based on neural network disturbance observer[J]. Control and Decision, 2008, 23(3): 283-287 (in Chinese). 陈谋, 邹庆元, 姜长生, 等. 基于神经网络干扰观测器的动态逆飞行控制[J]. 控制与决策, 2008, 23(3): 283-287.
[17] LI F, HU J B, WU J, et al. Dynamic surface control with nonlinear disturbance observer for uncertain flight dynamic system[J]. Transactions of Nanjing University of Aeronautics and Astronautics, 2015, 32(4): 469-476.

Options

Outlines

模态框（Modal）标题

Abstract

Cite this article

References