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Trophallaxis network control approach to formation flight of multiple unmanned aerial vehicles 被引量:16

Trophallaxis network control approach to formation flight of multiple unmanned aerial vehicles
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摘要 A novel network control method based on trophallaxis mechanism is applied to the formation flight problem for multiple unmanned aerial vehicles(UAVs).Firstly,the multiple UAVs formation flight system based on trophallaxis network control is given.Then,the model of leader-follower formation flight with a virtual leader based on trophallaxis network control is presented,and the influence of time delays on the network performance is analyzed.A particle swarm optimization(PSO)-based formation controller is proposed for solving the leader-follower formation flight system.The proposed method is applied to five UAVs for achieving a 'V' formation,and a series of experimental results show its feasibility and validity.The proposed control algorithm is also a promising control strategy for formation flight of multiple unmanned underwater vehicles(UUVs),unmanned ground vehicles(UGVs),missiles and satellites. A novel network control method based on trophaUaxis mechanism is applied to the formation flight problem for multiple un- manned aerial vehicles (UAVs). Firstly, the multiple UAVs formation flight system based on trophallaxis network control is given. Then, the model of leader-follower formation flight with a virtual leader based on trophallaxis network control is pre- sented, and the influence of time delays on the network performance is analyzed. A particle swarm optimization (PSO)-based formation controller is proposed for solving the leader-follower formation flight system. The proposed method is applied to five UAVs for achieving a 'V' formation, and a series of experimental results show its feasibility and validity. The proposed control algorithm is also a promising control strategy for formation flight of multiple unmanned underwater vehicles (UUVs), unmanned ground vehicles (UGVs), missiles and satellites.
出处 《Science China(Technological Sciences)》 SCIE EI CAS 2013年第5期1066-1074,共9页 中国科学(技术科学英文版)
基金 supported by the National Natural Science Foundation of China(Grant Nos.61273054,60975072 and 60604009) the National Basic Research Program of China("973"Project)(Grant No.2013CB035503) the Program for New Century Excellent Talents in University of China(Grant No.NCET-10-0021) the Aeronautical Foundation of China(Grant No.20115151019)
关键词 卫星编队飞行 网络控制 无人机 无人水下航行器 无人地面车辆 飞行系统 无人飞行器 粒子群优化 unmanned aerial vehicle (UAV), trophaHaxis, network control, formation flight, particle swarm optimization (PSO)
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  • 1YANG LingYu1, FAN YanMing2, SHAO Shan2, ZHONG YouWu1 & SHEN GongZhang1 1 Department of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China,2 Shenyang Aircraft Design and Research Institute, Shenyang 110035, China.Control allocation and management of redundant control effectors based on bases sequenced optimal method[J].Science China(Technological Sciences),2010,53(2):577-583. 被引量:6
  • 2DUAN HaiBin 1 ,SHAO Shan 2 ,SU BingWei 3 &ZHANG Lei 41 State Key Laboratory of Science and Technology on Holistic Flight Control,School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics,Beijing 100191,China,2 Flight Control Department,Shenyang Aircraft Design and Research Institute,Shenyang 110035,China,3 Beijing Institute of Near Space Vehicle’s System Engineering,Beijing 100076,China,4Integration and Project Section,Air Force Equipment Academy,Beijing 100085,China.New development thoughts on the bio-inspired intelligence based control for unmanned combat aerial vehicle[J].Science China(Technological Sciences),2010,53(8):2025-2031. 被引量:32
  • 3Hai-bin Duan,Xiang-yin Zhang,Jiang Wu,Guan-jun MaSchool of Automation Science and Electrical Engineering,Beihang University,Beijing 100191,P.R.China.Max-Min Adaptive Ant Colony Optimization Approach to Multi-UAVs Coordinated Trajectory Replanning in Dynamic and Uncertain Environments[J].Journal of Bionic Engineering,2009,6(2):161-173. 被引量:33
  • 4王芳.蚁群算法的原理及其应用[J].潍坊教育学院学报,2005,18(2):70-72. 被引量:7
  • 5付国江,王少梅,刘舒燕,李宁.改进的速度变异粒子群算法[J].计算机工程与应用,2006,42(13):48-50. 被引量:15
  • 6Acosta D M, Kumar K K, Kaneshige J T. Adaptive control for ESTOL design abstraction-performance analysis. In: 46th AIAA Aerospace Sciences Meeting and Exhibit Reno, Nevada, 2008.
  • 7Denham J, Paines J. Converging on a precision Hover control strategy for the F-35B STOVL aircraft. In: AIAA Guidance, Navigation and Control Conference and Exhibit, Honolulu, Hawaii, 2008.
  • 8Isidori A, Astofi A. Disturbance attenuation and Hc~ control via measurement feedback in nonlinear systems. IEEE Trans Automat Control 1992, 37:1283-1293.
  • 9Tanaka K, |keda T, Wang H O. Robust stabilization of a class of uncertain nonlinear systems via fuzzy control: quadratic stabilization, H-infinity control theory, and linear matrix inequalities. IEEE Trans Fuzzy Syst, 1996, 4:1-13.
  • 10Tanaka K, Ikeda T, Wang H. Design of fuzzy control systems based on relaxed LMI stability conditions. In: Proc 3, IEEE Conf on Decision and Control, Kobe, Japan, 1996. 598 603.

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