Full Text:   <273>

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CLC number: TN953; TP391.41

On-line Access: 2020-10-14

Received: 2019-11-12

Revision Accepted: 2020-01-03

Crosschecked: 2020-07-28

Cited: 0

Clicked: 361

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Rui Zhou

https://orcid.org/0000-0003-2476-1130

Jiang Zhao

https://orcid.org/0000-0002-9873-156X

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Frontiers of Information Technology & Electronic Engineering  2020 Vol.21 No.10 P.1494-1503

http://doi.org/10.1631/FITEE.1900617


Multi-UAV cooperative target tracking with bounded noise for connectivity preservation


Author(s):  Rui Zhou, Yu Feng, Bin Di, Jiang Zhao, Yan Hu

Affiliation(s):  School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China; more

Corresponding email(s):   jzhao@buaa.edu.cn

Key Words:  Multi-UAV cooperative target tracking, Network connectivity, Kalman consensus filter, Bounded noise, Connectivity preservation


Rui Zhou, Yu Feng, Bin Di, Jiang Zhao, Yan Hu. Multi-UAV cooperative target tracking with bounded noise for connectivity preservation[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(10): 1494-1503.

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A1 - Yan Hu
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Abstract: 
We investigate cooperative target tracking of multiple unmanned aerial vehicles (UAVs) with a limited communication range. This is an integration of UAV motion control, target state estimation, and network topology control. We first present the communication topology and basic notations for network connectivity, and introduce the distributed kalman consensus filter. Then, convergence and boundedness of the estimation errors using the filter are analyzed, and potential functions are proposed for communication link maintenance and collision avoidance. By taking stable target tracking into account, a distributed potential function based UAV motion controller is discussed. Since only the estimation of the target state rather than the state itself is available for UAV motion control and UAV motion can also affect the accuracy of state estimation, it is clear that the UAV motion control and target state estimation are coupled. Finally, the stability and convergence properties of the coupled system under bounded noise are analyzed in detail and demonstrated by simulations.

有界噪声下保通信连接的多无人机分布式协同目标跟踪

周锐1,冯禹1,邸斌2,赵江1,胡炎1,3
1北京航空航天大学自动化科学与电气工程学院,中国北京市,100191
2中国人民解放军军事科学院国防科技创新研究院,中国北京市,100171
3中国电子科技集团有限公司航空航天信息应用重点实验室,中国石家庄市,050081

摘要:本文研究通信距离受限的多无人机协同目标跟踪问题。该问题集成了无人机运动控制、目标状态估计和网络拓扑控制。首先,介绍用于描述网络连通性的通信拓扑和基本符号,以及分布式卡尔曼一致性滤波器。其次,分析基于滤波器的估计误差收敛性和有界性,采用势函数方法实现通信连接保持和防撞控制。在考虑稳定跟踪的基础上,设计基于势函数的分布式无人机运动控制器。由于无人机仅能获得目标状态的估计值而非真实值,且其运动也会影响状态估计精度,因此目标状态估计与无人机运动控制是耦合的。最后,详细分析耦合系统在有界噪声下的稳定性和收敛性,并进行仿真验证。

关键词:多无人机协同目标跟踪;网络连通;卡尔曼一致性滤波;有界噪声;连通性保持

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Ajorlou A, Momeni A, Aghdam AG, 2010. A class of bounded distributed control strategies for connectivity preservation in multi-agent systems. IEEE Trans Autom Contr, 55(12):2828-2833.

[2]Casbeer DW, Beard R, 2009a. Distributed information filtering using consensus filters. American Control Conf, p.1882-1887.

[3]Casbeer DW, Beard R, 2009b. Multi-static radar target tracking using information consensus filters. AIAA Guidance, Navigation, and Control Conf, p.1-9.

[4]Godsil C, Royle G, 2001. Algebraic Graph Theory. Springer-Verlag, New York, USA.

[5]Ji M, Egerstedt M, 2007. Distributed coordination control of multiagent systems while preserving connectedness. IEEE Trans Robot, 23(4):693-703.

[6]Kan Z, Dani AP, Shea JM, et al., 2012. Network connectivity preserving formation stabilization and obstacle avoidance via a decentralized controller. IEEE Trans Autom Contr, 57(7):1827-1832.

[7]Kim Y, Mesbahi M, 2006. On maximizing the second smallest eigenvalue of a state-dependent graph Laplacian. IEEE Trans Autom Contr, 51(1):116-120.

[8]Kim Y, Gu DW, Postlethwaite I, 2010. Robust target tracking using distributed unmanned aerial vehicle networks. Proc Inst Mech Eng Part G J Aerosp Eng, 224(4):417-426.

[9]Li TC, Fan HQ, García J, et al., 2019. Second-order statistics analysis and comparison between arithmetic and geometric average fusion: application to multi-sensor target tracking. Inform Fus, 51:233-243.

[10]Lim S, Kim Y, Lee D, et al., 2013. Standoff target tracking using a vector field for multiple unmanned aircrafts. J Intell Robot Syst, 69(1-4):347-360.

[11]Liu QY, Wang ZD, He X, et al., 2018. On Kalman-consensus filtering with random link failures over sensor networks. IEEE Trans Autom Contr, 63(8):2701-2708.

[12]Liu S, Zhang HM, 2011. Optimal Estimation Theory. Science Press, Beijing (in Chinese).

[13]Ma LL, Hovakimyan N, 2013. Cooperative target tracking in balanced circular formation: multiple UAVs tracking a ground vehicle. American Control Conf, p.5386-5391.

[14]Olfati-Saber R, 2006. Flocking for multi-agent dynamic systems: algorithms and theory. IEEE Trans Autom Contr, 51(3):401-420.

[15]Olfati-Saber R, 2007a. Distributed Kalman filtering for sensor networks. Proc 46th IEEE Conf on Decision and Control, p.12-14.

[16]Olfati-Saber R, 2007b. Distributed tracking for mobile sensor networks with information-driven mobility. American Control Conf, p.728-734.

[17]Olfati-Saber R, 2009. Kalman-consensus filter: optimality, stability, and performance. Proc 48th IEEE Conf on Decision and Control held jointly with 28th Chinese Control Conf, p.7036-7042.

[18]Olfati-Saber R, Jalalkamali P, 2012. Coupled distributed estimation and control for mobile sensor networks. IEEE Trans Autom Contr, 57(10):2609-2614.

[19]Oriolo G, de Luca A, Vendittelli M, 2002. WMR control via dynamic feedback linearization: design, implementation, and experimental validation. IEEE Trans Contr Syst Technol, 10(6):835-852.

[20]Stachura M, Frew EW, 2011. Cooperative target localization with a communication-aware unmanned aircraft system. J Guid Contr Dynam, 34(5):1352-1362.

[21]Tanner HG, Jadbabaie A, Pappas GJ, 2007. Flocking in fixed and switching networks. IEEE Trans Autom Contr, 52(5):863-868.

[22]Wang L, Wang XF, Hu XM, 2015. Connectivity maintenance and distributed tracking for double-integrator agents with bounded potential functions. Int J Robust Nonl Contr, 25(4):542-588.

[23]Wang YT, Li JB, Sun Q, 2013. Coordinated target tracking by distributed unscented information filter in sensor networks with measurement constraints. Math Probl Eng, 2013:402732.

[24]Wen G, Duan Z, Su H, et al., 2012. A connectivity-preserving flocking algorithm for multi-agent dynamical systems with bounded potential function. IET Contr Theory Appl, 6(6):813-821.

[25]Yan MD, Zhu X, Zhang XX, et al., 2017. Consensus-based three-dimensional multi-UAV formation control strategy with high precision. Front Inform Technol Electron Eng, 18(7):968-977.

[26]Yang P, Freeman RA, Gordon GJ, et al., 2010. Decentralized estimation and control of graph connectivity for mobile sensor networks. Automatica, 46(2):390-396.

[27]Yu ZQ, Liu ZX, Zhang YM, et al., 2019. Decentralized fault-tolerant cooperative control of multiple UAVs with prescribed attitude synchronization tracking performance under directed communication topology. Front Inform Technol Electron Eng, 20(5):685-700.

[28]Zavlanos MM, Pappas GJ, 2007. Potential fields for maintaining connectivity of mobile networks. IEEE Trans Robot, 23(4):812-816.

[29]Zavlanos MM, Pappas GJ, 2008. Distributed connectivity control of mobile networks. IEEE Trans Robot, 24(6):1416-1428.

[30]Zavlanos MM, Tanner HG, Jadbabaie A, et al., 2009. Hybrid control for connectivity preserving flocking. IEEE Trans Autom Contr, 54(12):2869-2875.

[31]Zavlanos MM, Egerstedt MB, Pappas GJ, 2011. Graph-theoretic connectivity control of mobile robot networks. Proc IEEE, 99(9):1525-1540.

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