[1]ZHANG Tianjie,DUAN Haibin.A modified consensus algorithm for multi-UAV formations based on pigeon-inspired optimization with a slow diving strategy[J].智能系统学报,2017,12(4):570-581.[doi:10.11992/tis.201604006]
 ZHANG Tianjie,DUAN Haibin.A modified consensus algorithm for multi-UAV formations based on pigeon-inspired optimization with a slow diving strategy[J].CAAI Transactions on Intelligent Systems,2017,12(4):570-581.[doi:10.11992/tis.201604006]

A modified consensus algorithm for multi-UAV formations based on pigeon-inspired optimization with a slow diving strategy

[1] RYAN A, ZENNARO M, HOWELL A, et al. An overview of emerging results in cooperative UAV control[C]//The proceedings of 43rd IEEE Conference on Decision and Control. atlantis, Paradise Island, Bahamas, 2004:602-607
[2] ZHA W, CHEN J, PENG Z. Dynamic multi-team antagonistic games model with incomplete information and its application to multi-UAV[J]. IEEE/CAA Journal of automatica sinica, 2015, 2(1):74-84
[3] CHAUMETTE S, LAPLACE R, MAZEL C. CARUS, an operational retasking application for a swarm of autonomous UAVs:first return on experience[C]//The proceedings of 2011 Military Communications Conference Track 5 Communications and Network Systems. Baltimore, Maryland, USA, 2011:2003-2010.
[4] RASCHE C, STERN C, KLEINJOHANN L, et al. A distributed multi-UAV path planning approach for 3D environments[C]//The proceedings of the 5th International Conference on Automation, Robotics and Applications. Wellington, New Zealand, 2011:7-12.
[5] GIULIETTI F, INNOCENTI M, NAPOLITANO M, et al. Dynamic and control issues of formation flight[J]. Aerospace science and technology, 2005, 9(1):65-71.
[6] CRUZ J. Leader-follower strategies for multilevel systems[J]. IEEE transactions on automatic control, 1978, 23(2):244-255.
[7] PAUL T, KROGSTAD T, GRAVDAHL J. Modelling of UAV formation flight using 3D potential fields[J]. Simulation modelling practice and theory, 2008, 16(9):1240-1254.
[8] RAO V, SINHA N. A sliding mode controller for aircraft simulated entry into spin[J]. Aerospace science and technology, 2013, 8(1):154-163.
[9] REN W, BEARD R, ATKINS E. Information consensus in multivehicle cooperative control:collective group behavior through local interaction[J]. IEEE control systems, 2007, 27(2):71-82.
[10] VICSEK T. Universal patterns of collective motion from minimal models of flocking[C]//The proceedings of the 2nd IEEE International Conference on Self-Adaptive and Self-Organizing Systems. Venice, Italy, 2008:3-11.
[11] REN W, BEARD R W, MCLAIN T W. Coordination variables and consensus building in multiple vehicle systems[J]. Lecture notes in control and information sciences, 2005, 309:439-442.
[12] REN W, BEARD R W. Consensus seeking in multiagent systems under dynamically changing interaction topologies[J]. IEEE transactions on automatic control, 2005, 50(5):655-661.
[13] SORENSEN N, REN W. A unified formation control scheme with a single or multiple leaders[C]//The proceedings of American Control Conference. New York City, USA, 2007:5412-5418.
[14] REN W, SORENSEN N. Distributed coordination architecture fo r multi-robot formation control[J]. Robotics and autonomous systems, 2008, 56(4):324-333.
[15] DUAN H, QIAO P. Pigeon-inspired optimization:a new swarm intelligence optimizer for air robot path planning[J]. International journal of intelligence computation and cybernetics, 2014, 7(1):24-37.
[16] GUILFORD T, ROBERTS S, BIRO D, et al. Positional entropy during pigeon homing Ⅱ:navigational interpretation of Bayesian latent state models[J]. Journal of theoretical biology, 2004, 227(1):25-38.
[17] LI C, DUAN H. Target detection approach for UAVs via improved pigeon-inspired optimization and edge potential function[J]. Aerospace science and technology, 2014, 39:352-360.
[18] ZHANG B, DUAN H. Three-dimensional path planning for uninhabited combat aerial vehicle based on predator-prey pigeon-inspired optimization in dynamic environment[J]. IEEE/ACM transactions on computation and biology bioinformaion, 2017, 14(1):97-107
[19] DUAN H, WANG X. Echo state networks with orthogonal pigeon-inspired optimization for image restoration[J]. IEEE transactions on neural networks and learning Systems, 2016, 27(11):2413-2425.
[20] ZHANG S, DUAN H. Gaussian Pigeon-inspired optimization approach to orbital spacecraft formation reconfiguration[J]. Chinese journal of aeronautics, 2015, 28(1):200-205.
[21] ZHAO J, ZHOU R. Pigeon-inspired optimization applied to constrained gliding trajectories[J]. Nonlinear dynamics, 2015, 82(4):1781-1795.


基金项目:Natural Science Foundation of China under Grant(61333004).
作者简介:ZHANG Tianjie was born in 1992.He received his Bachelor’s degree from BUAA in 2015 and now he is a graduate student in BUAA.His main research focuses on aircraft mission planning;DUAN Haibin was born in Shandong,China,in 1976.He received the Ph.D.degree from Nanjing University of Aeronautics and Astronautics,Nanjing,China,in 2005.He is currently a Full Professor with the School of Automation Science and Electrical Engineering,Beihang University (formerly Beijing University of Aeronautics and Astronautics),Beijing,China,where he is the Head of the Bio-inspired Autonomous Flight Systems Research Group.He has authored or coauthored more than 70 publications.His research interests are multiple unmanned-aerial-vehicle autonomous formation control and biological computer vision.
通讯作者:ZHANG Tianjie,E-mail:11031148@buaa.edu.cn.

更新日期/Last Update: 2017-08-25
Copyright © 《 智能系统学报》 编辑部
地址:(150001)黑龙江省哈尔滨市南岗区南通大街145-1号楼 电话:0451- 82534001、82518134 邮箱:tis@vip.sina.com