基于自适应方法的多无人机编队队形控制

doi:10.7527/S1000-6893.2019.23385

电子电气工程与控制

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基于自适应方法的多无人机编队队形控制

张佳龙, 闫建国, 张普

西北工业大学自动化学院, 西安 710129

收稿日期:2019-08-15 修回日期:2019-09-04 出版日期:2020-01-15 发布日期:2019-10-24
通讯作者: 闫建国 E-mail:yjg0311@nwpu.edu.cn
基金资助:
西北工业大学博士论文创新基金（CX201955）

Multi-UAV formation forming control based on adaptive method under wind field disturbances

ZHANG Jialong, YAN Jianguo, ZHANG Pu

School of Automation, Northwestern Polytechnical University, Xi'an 710129, China

Received:2019-08-15 Revised:2019-09-04 Online:2020-01-15 Published:2019-10-24
Supported by:
Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University (CX201955)

摘要/Abstract

摘要： 针对"长机-僚机"近距编队队形因风场扰动而不能保持期望队形的问题，首先，提出了一种自适应队形保持控制的方法，该方法可用于抵消因风场不确定性对无人机的横侧向和前行方向所产生的距离误差，同时能够保持无人机编队稳定飞行。其次，由于风场的不确定性会引起"长机-僚机"之间的动力学发生变化，因此设计了一种基于"长机-僚机"相对运动模型的自适应控制律用以估计风场在3个方向的大小，进而控制无人机之间的相对运动以消除风场不确定性所产生的距离误差并保持速度的一致性，最终实现保持期望的队形。再次，通过构建合理的李雅普诺夫函数，证明无人机编队在风场干扰下能够保持编队稳定飞行，同时"长机-僚机"之间相对横向、横侧向以及纵向的距离误差均接近零。最后，通过仿真验证：所提出的自适应控制方法具有良好的鲁棒性，这为工程实践提供理论依据。

关键词: “长机-僚机”近距编队, 风场扰动, 自适应控制, 队形保持, 鲁棒性

Abstract: The "leader-follower" closed formation is unable to keep the desired formation due to wind disturbances. To solve this problem, an adaptive formation keeping control method is proposed to counteract the lateral and forward distance error due to the uncertain wind disturbances and to maintain the desired formation flight. Since uncertain wind disturbances change the dynamics between the leader and the follower, this paper designs an adaptive control law based on the "leader-follower" model to accurately estimate the magnitude and direction of the wind in three-dimensional space. Subsequently, it helps control the relative motion between UAVs to eliminate the distance error and keep the consensus of velocity, which can achieve the desired formation. It is proved that the "leader-follower" formation can keep flight-stability in windy field environment, and the relative lateral, forward, and longitudinal distance errors between them are close to zero according to a reasonable Lyapunov function. The simulation results show that the proposed adaptive control method has good robustness, providing a theoretical basis for engineering practice.

Key words: “leader-follower” closed formation, windy filed disturbances, adaptive control, formation keeping, robustness

中图分类号:

V211.3
TP273

张佳龙, 闫建国, 张普. 基于自适应方法的多无人机编队队形控制[J]. 航空学报, 2020, 41(1): 323385-323385.

ZHANG Jialong, YAN Jianguo, ZHANG Pu. Multi-UAV formation forming control based on adaptive method under wind field disturbances[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(1): 323385-323385.

参考文献 35

[1]	SHAMES I, FIDAN B, ANDERSON B D O. Close target reconnaissance using autonomous UAV formations[C]//47th IEEE Conference on Decision and Control. Piscataway, NJ:IEEE Press, 2009.
[2]	MCFARLANE C, RICHARDSON T, JONES C. Cooperative control during boom air-to-air refueling[C]//AIAA Guidance, Navigation and Control Conference and Exhibit. Reston, VA:AIAA, 2007.
[3]	张佳龙,闫建国,张普, 等. 基于改进人工势场的无人机编队避障控制研究[J]. 西安交通大学学报, 2018, 52(11):116-123. ZHANG J L, YAN J G, ZHANG P, et al. Study on the collision avoidance of UAV cooperative formation with improved artificial potential field[J]. Journal of Xi'an Jiaotong University, 2018, 52(11):116-123(in Chinese).
[4]	常凯, 黄考利, 马代亮. 无人机编队对地面目标追踪问题研究[J]. 电光与控制, 2016(6):11-15. CHANG K, HUANG K L, MA D L. Ground moving target tracking by formation of UAVs[J]. Electronics Optics & Control, 2016(6):11-15(in Chinese).
[5]	DOGAN A, VENKATARAMANAN S, BLAKE W. Modeling of aerodynamic coupling between aircraft in close proximity[J]. Journal of Aircraft, 2005, 42(4):941-955.
[6]	SABAN D, WHIDBORNE J F, COOKE A K. Simulation of wake vortex effects for UAVs in close formation flight[J]. The Aeronautical Journal, 2009, 113(1149):727-738.
[7]	雷旭升, 陶冶. 小型无人飞行器风场扰动自适应控制方法[J]. 航空学报, 2010, 31(6):1171-1176. LEI X S, TAO Y. Adaptive control for small unmanned aerial vehicle under wind disturbance[J]. Acta Aeronautica et Astronautica Sinica, 2010, 31(6):1171-1176(in Chinese).
[8]	屈耀红, 凌琼, 闫建国, 等. 无人机DR/GPS/RP导航中风场估计仿真[J]. 系统仿真学报, 2009(7):1822-1825. QU Y H, LING Q, YAN J G, et al. Wind field estimation simulation technology in DR/GPS/RP integrated navigation of UAV[J]. Journal of System Simulation, 2009(7):1822-1825(in Chinese).
[9]	屈耀红. 小型无人机航迹规划及组合导航关键技术研究[D]. 西安:西北工业大学, 2006. QU Y H. Study on the key techniques of trajectory planning and integrated navigation of UAV[D]. Xi'an:Xi'an Northwestern Polytechnical University, 2006(in Chinese).
[10]	CHEN W H, YANG J, GUO L, et al. Disturbance-observer-based control and related methods-An overview[J]. IEEE Transactions on Industrial Electronics, 2016, 63(2):1083-1095.
[11]	陈侠, 鹿振宇. 风场干扰下基于一致性卡尔曼滤波的UAV编队控制算法[J]. 兵工自动化, 2013(10):28-32. CHEN X, LU Z Y. Based on consensus Kalman filtering under wind interference[J]. Ordnance Industry Automation, 2013(10):28-32(in Chinese).
[12]	YUAN K, LI H X, CAO J. Robust stabilization of the distributed parameter system with time delay via fuzzy control[J]. IMA Journal of Mathematical Control & Information, 2018, 31(1):51-72.
[13]	ZHAO Z, WANG X, ZHANG C, et al. Neural network based boundary control of a vibrating string system with input deadzone[J]. Neurocomputing, 2018, 275:1021-1027.
[14]	YUAN S, ZHAO C, GUO L. Uncoupled PID control of coupled multi-agent nonlinear uncertain systems[J]. Journal of Systems Science & Complexity, 2018, 31(1):4-21.
[15]	ISLAM S, LIU P X, EL S A. Robust control of four-rotor unmanned aerial vehicle with disturbance uncertainty[J]. IEEE Transactions on Industrial Electronics, 2015, 62(3):1563-1571.
[16]	BREZOESCU A, ESPINOZA T, CASTILLO P, et al. Adaptive trajectory following for a fixed-wing UAV in presence of crosswind[J]. Journal of Intelligent & Robotic Systems, 2013, 69(1-4):257-271.
[17]	ZHANG Q, LIU H. Robust design of close formation flight control via uncertainty and disturbance estimator[C]//AIAA Guidance, Navigation, and Control Conference. Reston, VA:AIAA, 2016.
[18]	ZHANG Q R, LIU H H. Aerodynamic model-based robust adaptive control for close formation flight[J]. Aerospace Science and Technology, 2018, 79:5-16.
[19]	LEE D, KIM S, SUK J. Formation flight of unmanned aerial vehicles using track guidance[J]. Aerospace Science and Technology, 2018(76):412-420.
[20]	席峰, 刘中. 基于信息矩阵加权一致策略的分布式Kalman滤波器[J]. 信息与控制, 2010, 39(2):194-199. XI F, LIU Z. Distributed Kalman filter with information matrix weighted consensus strategies[J]. Information and Control, 2010, 39(2):194-199(in Chinese).
[21]	SPANOS P D, SANER O R, MURRAY R M. Dynamic consensus on mobile networks[C]//Proceeding of the 16th IFAC World Congress, 2005.
[22]	杨文, 侍洪波, 汪小帆. 卡尔曼一致滤波算法综述[J]. 控制与决策, 2011, 26(4):481-488. YANG W, SHI H B, WANG X F. A survey of consensus based Kalman filtering algorithm[J]. Control and Decision, 2011, 26(4):481-488(in Chinese).
[23]	王义. 基于一致性Unsented卡尔曼滤波的多机器人定位[J]. 计算机技术与发展, 2011, 21(3):24-27. WANG Y. Localization for multi-robot based on Unsented Kalman-consensus filter[J]. Computer Technology and Development, 2011, 21(3):24-27(in chinese).
[24]	吴正平, 关治洪, 吴先用. 基于一致性理论的多机器人系统队形控制[J]. 控制与决策, 2007, 22(11):1241-1244. WU Z P, GUAN Z H, WU X Y. Consensus based formation control of multi-robot system[J]. Control and Decision, 2007, 22(11):1241-1244(in Chinese).
[25]	REN W. Trajectory tracking control for a miniature fixed-wing unmanned air vehicle[J]. International Journal of Systems Science, 2007, 38(4):361-368.
[26]	ZHANG Q, LIU H T, ZHANG Q, et al. Aerodynamics modeling and analysis of close formation flight[J]. Journal of Aircraft, 2017, 54(1):2192-2204.
[27]	GU Y, SEANOR B, CAMPA G, et al. Design and flight testing evaluation of formation control laws[J]. IEEE Transactions on Control Systems Technology, 2006, 14(6):1105-1112.
[28]	李炳乾, 董文瀚, 马小山. 无人机编队保持反步容错控制[J]. 兵工学报, 2018, 39(11):95-107. LI B Q, DONG W H, MA X S. Back-stepping fault-tolerant control for keeping the formation of unmanned aerial vehicles[J]. Acta Armamentarii, 2018, 39(11):95-107(in Chinese).
[29]	吴森堂. 飞行控制系统[M]. 北京:北京航空航天大学出版社, 2013. WU S T. Flight control system[M]. Beijing:Beihang University Press, 2013(in Chinese).
[30]	SLOTINE J J E, LI W P. Applied nonlinear control[M]. London:Pearson, 1991.
[31]	龙涛, 苏菲, 朱华勇, 等. 无人作战飞机操作员控制台仿真系统[J]. 系统仿真学报, 2006, 18(7):1835-1839. LONG T, SU F, ZHU H Y, et al. Operator console simulation system of unmanned combat aerial vehicles[J]. Journal of System Simulation, 2006, 18(7):1835-1839(in Chinese).
[32]	王晋云,魏瑞轩,董志兴, 等. 无人机编队飞行控制仿真研究[J]. 火力与指挥控制,2010, 35(3):34-38. WANG J Y, WEI R X, DONG Z X, et al. Research on formation flight control of cooperative UAV[J]. Fire Control & Command Control,2010, 35(3):34-38(in Chinese).
[33]	LIU D, YANG G H. Prescribed performance model-free adaptive integral sliding mode control for discrete-time nonlinear systems[J]. IEEE Transactions on Neural Networks and Learning Systems, 2018, 30(7):2222-2230.
[34]	LIAO B, ZHANG Q, LI J. Integrated sliding mode control and neural networks based packet disordering prediction for nonlinear networked control systems[J]. IEEE Transactions on Neural Networks and Learning Systems, 2018, 3(4):972-977.
[35]	WU Z, WANG Z, YANG Y, et al. Adaptive back-stepping control of spacecraft attitude with variable speed control moment gyroscopes[C]//Control Conference. Piscataway, NJ:IEEE Press, 2013.

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

基于自适应方法的多无人机编队队形控制

Multi-UAV formation forming control based on adaptive method under wind field disturbances

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