Electronics and Electrical Engineering and Control

Improved consensus-based algorithm for unmanned aerial vehicle formation control

  • WU Yu ,
  • LIANG Tianjiao
Expand
  • 1. College of Aerospace Engineering, Chongqing University, Chongqing 400044, China;
    2. Key Laboratory of Aviation Science and Technology on Fighter Integrated Simulation, Chengdu 610091, China

Received date: 2020-01-17

  Revised date: 2020-02-11

  Online published: 2020-05-21

Supported by

The fundamental Research Funds for the Central Universities (2019CDJGFHK001)

Abstract

Formation flight refers to the state in which multiple UAVs keep flying in a specific configuration. Compared to single UAVs, UAV formation can increase the search area, enhance flight performance and raise the success rate of missions. UAV formation control is the premise for a safe and efficient mission. In this paper, the standard consensus algorithm is improved according to the characteristics of the UAV motion model and the demand of actual flight, and an improved consensus-based formation control algorithm is proposed. First, the 3-DOF kinetic equations of UAVs are established based on the decoupled autopilot model, and the constraints on acceleration, velocity and angular rates are defined considering the maneuverability and flight performance of UAVs. The formation control is also carried out in the horizonal plane and vertical direction respectively. Based on the state control, the DOFs of UAVs are transformed using the geometrical relationship between different states of UAVs, and the formation control algorithm is designed integrating the configuration information. Furthermore, a constraint handling strategy named 'minimum adjustment’ is developed to enable the command signals to meet all the constraints. The collision between UAVs is avoided by optimizing the climbing acceleration of UAVs with the Particle Swarm Optimization (PSO) algorithm. Simulation results demonstrate the ability of the proposed formation control algorithm to form or change the formation. The states and configuration of the UAV formation can quickly converge to the specific values, and the states of UAVs satisfy all the constraints.

Cite this article

WU Yu , LIANG Tianjiao . Improved consensus-based algorithm for unmanned aerial vehicle formation control[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020 , 41(9) : 323848 -323848 . DOI: 10.7527/S1000-6893.2020.23848

References

[1] 张佳龙, 闫建国, 张普. 基于反步推演法的多机编队队形重构控制[J]. 航空学报, 2019, 40(11):323177. ZHANG J L, YAN J G, ZHANG P. Multi-UAV formation forming reconfiguration control based on back-stepping method[J]. Acta Aeronautica et Astronautica Sinica, 2019, 40(11):323177(in Chinese).
[2] 宗群, 王丹丹, 邵士凯, 等. 多无人机协同编队飞行控制研究现状及发展[J]. 哈尔滨工业大学学报, 2017, 49(3):1-14. ZONG Q, WANG D D, SHAO S K, et al. Research status and development of multi UAV coordinated formation flight control[J]. Journal of Harbin Institute of Technology, 2017, 49(3):1-14(in Chinese).
[3] SHAO S, PENG Y, HE C, et al. Efficient path planning for UAV formation via comprehensively improved particle swarm optimization[J]. ISA Transactions, 2019, 97:415-430.
[4] HARIKUMAR K, SENTHILNATH J, SUNDARAM S. Multi-UAV oxyrrhis marina-inspired search and dynamic formation control for forest firefighting[J]. IEEE Transactions on Automation Science and Engineering, 2018, 16(2):863-873.
[5] JU C, SON H I. A distributed swarm control for an agricultural multiple unmanned aerial vehicle system[J]. Proceedings of the Institution of Mechanical Engineers, Part I:Journal of Systems and Control Engineering, 2019:0959651819828460.
[6] 王晶,顾维博,窦立亚. 基于Leader-Follower的多无人机编队轨迹跟踪设计[J]. 航空学报, 2020, 41(S1):723758. WANG J, GU W B, DOU L Y. Leader-Follower formation control of multiple UAVs with trajectory tracking design[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41(S1):723758(in Chinese).
[7] JIN X Z, WANG S F, YANG G H, et al. Robust adaptive hierarchical insensitive tracking control of a class of leader-follower agents[J]. Information Sciences, 2017, 406:234-247.
[8] EBEGBULEM J, GUAY M. Distributed control of multi-agent systems over unknown communication networks using extremum seeking[J]. Journal of Process Control, 2017, 59:37-48.
[9] JIN X, HADDAD W M. An adaptive control architecture for leader-follower multiagent systems with stochastic disturbances and sensor and actuator attacks[J]. International Journal of Control, 2019, 92(11):2561-2570.
[10] 安永跃, 李淑琴. 基于行为规划的多机器鱼编队策略的研究[J]. 计算机仿真, 2013, 30(11):369-373. AN Y Y, LI S Q. Study of multiple robotic fishes formation strategy based on behavior planning method[J]. Computer Simulation, 2013, 30(11):369-373(in Chinese).
[11] 雷艳敏, 冯志彬, 宋继红. 基于行为的多机器人编队控制的仿真研究[J]. 长春大学学报, 2008(8):43-47. LEI Y M, FENG Z B, SONG J H. The simulation study on formation control of multi-robot system based on behaviors[J]. Journal of Changchun University, 2008(8):43-47(in Chinese).
[12] AHMAD S, FENG Z, HU G. Multi-robot formation control using distributed null space behavioral approach[C]//IEEE International Conference on Robotics & Automation. Piscataway:IEEE Press, 2014.
[13] 吕永申, 刘力嘉, 杨雪榕, 等. 人工势场与虚拟结构相结合的无人机集群编队控制[J]. 飞行力学, 2019, 37(3):43-47. LYU Y S, LIU L J, YANG X R, et al. Formation control of UAV swarm combining artificial potential field and virtual structure[J]. Flight Dynamics, 2019, 37(3):43-47(in Chinese).
[14] 王祥科, 李迅, 郑志强. 多智能体系统编队控制相关问题研究综述[J]. 控制与决策, 2013(11):4-16. WANG X K, LI X, ZHENG Z Q. Survey of developments on multi-agent formation control related problems[J]. Control and Decision, 2013(11):4-16(in Chinese).
[15] REN W. Consensus based formation control strategies for multi-vehicle systems[C]//2006 American Control Conference. Piscataway:IEEE Press, 2006:6.
[16] REN W. Consensus strategies for cooperative control of vehicle formations[J]. IET Control Theory & Applications, 2007, 1(2):505-512.
[17] 李静宇, 姚志军, 田睿. 一致性特征点匹配在目标跟踪中的应用[J]. 电子测量技术, 2015(10):28-31. LI J Y, YAO Z J, TIAN R. Target tracking based on consistency feature points matching[J]. Electronic Measurement Technology, 2015(10):28-31(in Chinese).
[18] 刘瑜, 刘俊, 徐从安, 等. 非均匀拓扑网络中的分布式一致性状态估计算法[J]. 系统工程与电子技术, 2018, 40(9):26-34. LIU Y, LIU J, XU C A, et al. Distributed consensus state estimation algorithm in asymmetrical networks[J]. Systems Engineering and Electronics, 2018, 40(9):26-34(in Chinese).
[19] 陈旿, 张鑫, 金鑫, 等. 一种多智能体协同信息一致性算法[J]. 航空学报, 2017, 38(12):321222. CHEN W, ZHANG X, JIN X, et al. A cooperative information consensus algorithm for multiagent system[J]. Acta Aeronautica et Astronautica Sinica, 2017, 38(12):321222(in Chinese).
[20] SUN F, TURKOGLU K. Nonlinear consensus strategies for multi-agent networks under switching topologies:Real-time receding horizon approach[J]. Aerospace Science and Technology, 2019, 87:323-330.
[21] KURIKI Y, NAMERIKAWA T. Consensus-based cooperative formation control with collision avoidance for a multi-UAV system[C]//2014 American Control Conference. Piscataway:IEEE Press, 2014:2077-2082.
[22] 王新民, 王晓燕. 无人机编队飞行技术[M]. 西安:西北工业大学出版社, 2015:149-232. WANG X M, WANG X Y. UAV formation flight technology[M]. Xi'an:Northwestern Polytechnical University Press, 2015:149-232(in Chinese).
[23] 王树禾. 图论[M]. 北京:科学出版社, 2004:5-6. WANG S H.Graph theory[M]. Beijing:Science Press, 2004:5-6.
[24] SHI Y, EBERHART R C. Parameter selection in particle swarm optimization[C]//International Conference on Evolutionary Programming.Berlin:Springer, 1998:591-600.
Outlines

/