Three-dimensional formation keeping of multi-UAV based on consensus

Xu Zhu , Xun-xun Zhang , Mao-de Yan , Yao-hong Qu

Journal of Central South University ›› 2017, Vol. 24 ›› Issue (6) : 1387 -1395.

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Journal of Central South University ›› 2017, Vol. 24 ›› Issue (6) : 1387 -1395. DOI: 10.1007/s11771-017-3543-4
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Three-dimensional formation keeping of multi-UAV based on consensus

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Abstract

Consensus is an emerging technique using neighbor-to-neighbor interaction to generate steering commands for cooperative control of multiple vehicles. A three-dimensional formation keeping strategy for multiple unmanned aerial vehicles (multi-UAV) is proposed based on consensus, aiming at maintaining a specified geometric configuration. A formation control algorithm with guidance and corresponding flight controllers is given, managing position and attitude, respectively. In order to follow a three-dimensional predefined flight path, by introducing the tracking orders as reference states into the consensus, the formation control algorithm is designed, following the predefined flight path and maintaining geometric configuration simultaneously. The flight controllers are constructed by nonlinear dynamic inverse, including attitude design and velocity design. With the whole system composed of a nonlinear six-degree-of-freedom UAV model, the formation control algorithm and the flight controllers, the formation keeping strategy is closed loop and with full states. In simulation, three-dimensional formation flight demonstrates the feasibility and effectiveness of the proposed strategy.

Keywords

multiple unmanned aerial vehicles / formation keeping / consensus / reference state / flight control

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Xu Zhu, Xun-xun Zhang, Mao-de Yan, Yao-hong Qu. Three-dimensional formation keeping of multi-UAV based on consensus. Journal of Central South University, 2017, 24(6): 1387-1395 DOI:10.1007/s11771-017-3543-4

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References

[1]

KimS, KimY. Trajectory optimization for unmanned aerial vehicle formation reconfiguration [J]. Engineering Optimization, 2014, 46(1): 84-106

[2]

ShiX-h, LiangQ-y, ZhangQ-j, WangJ, ShenX-qiang. Multi-UAV target tracking using DC-IMM estimate method [J]. Journal of Central South University: Science and Technology, 2013, 44(2): 52-57

[3]

SaskaM, VonsekV, KrajnkT, PeuilL. Coordination and navigation of heterogeneous MAV-UGV formations localized by a 'hawk-eye'-like approach under a model predictive control scheme [J]. International Journal of Robotics Research, 2014, 33(10): 1393-1412

[4]

DuanH-b, QiaoP-xin. Pigeon-inspired optimization: A new swarm intelligence optimizer for air robot path planning [J]. International Journal of Intelligent Computing and Cybernetics, 2014, 7(1): 24-37

[5]

BayezitI, FidanB. Distributed cohesive motion control of flight vehicle formations [J]. IEEE Transactions on Industrial Electronics, 2013, 60(12): 5763-5772

[6]

HoltJ, BiazS, YilmazL, AjiC A. A symbiotic simulation architecture for evaluating UAVs collision avoidance techniques [J]. Journal of Simulation, 2014, 8(1): 64-75

[7]

SperandioG, PauloA, HemerlyE M. Reconfiguration between longitudinal and circular formations for multi-UAV systems by using segments [J]. Journal of Intelligent and Robotic Systems: Theory and Applications, 2015, 78(2): 339-355

[8]

DongX-w, YuB-c, ShiZ-y, ZhongY-sheng. Time-varying formation control for unmanned aerial vehicles: Theories and applications [J]. IEEE Transactions on Control Systems Technology, 2015, 23(1): 340-348

[9]

YanD, ChenW, BaoS-yu. Decentralized formation control for multiple UAVs based on leader-following consensus with time-varying delays [C]//. Chinese Automation Congress, 2013, Piscataway, United States, IEEE Computer Society: 426431

[10]

SunT, XinMing. Multiple UAV target tracking using consensus-based distributed high degree cubature information filter [C]//. AIAA Guidance, Navigation, and Control Conference, 2015111

[11]

ZhuX, ZhangX-x, YouJ-y, YanM-d, QuY-hong. Swarm control of UAV close formation based on information consensus [J]. Acta Aeronautica et Astronautica Sinica, 2008, 36(12): 3919-3929

[12]

SeoJ, AhnC, KimY. Controller design for UAV formation flight using consensus based decentralized approach [C]//. AIAA Infotech at Aerospace Conference and Exhibit and AIAA Unmanned Unlimited Conference, 2009, Reston, American Institute of Aeronautics and Astronautics Inc: 111

[13]

ReihaneR, FarzanehA, KaroN. Time-varying formation control of a collaborative heterogeneous multi agent system [J]. Robotics and Autonomous Systems, 2014, 62(12): 1799-1805

[14]

ManatharaJ G, GhoseD. Rendezvous of multiple UAVs with collision avoidance using consensus [J]. Journal of Aerospace Engineering, 2012, 25(4): 480-489

[15]

JaimesB, AldoS, JamshidiM. Consensus-based and network control of UAVs [C]//. International Conference on System of Systems Engineering, 2010, Piscataway, United States, Institute of Electrical and Electronics Engineers: 16

[16]

WangJ-y, WeiR-x, DongZ-x, ZhouWei. Research on formation flight control of cooperative UAV [J]. Fire Control Command Control, 2010, 35(3): 34-38

[17]

BaiC, DuanH-b, LiC, ZhangY-peng. Dynamic multi-UAVs formation reconfiguration based on hybrid diversity-PSO and time optimal control [C]//. Proceedings of the IEEE Intelligent Vehicles Symposium, 2009, Piscataway, United States, Institute of Electrical and Electronics Engineers: 775779

[18]

WuS-t, FeiY-huaFlight control system [M], 2006, Beijing, Beihang University Press: 960

[19]

ZengYuNavigation control system of UAV[D], 2009, Xi’an, School of Automation, Northwestern Polytechnical University

[20]

RenW, BeardR WDistributed consensus in multi–vehicle cooperative control: theory and applications [M], 2007, New York, Springer Publishing Company: 3687

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