| Citation: | MA S H,ZHANG D,WANG M Y,et al. Directed interactive topology optimization design for multi-agent affine formation maneuver control[J]. Journal of Beijing University of Aeronautics and Astronautics,2025,51(4):1367-1376 (in Chinese) doi: 10.13700/j.bh.1001-5965.2023.0180 |
This paper investigated the directed interactive topology optimization design problem for multi-agent affine formation maneuver control. Firstly, by considering the optimization indexes such as information interaction cost and energy consumption during information spreading, a directed topology optimization model for affine formation maneuver was established, including topology structure construction and weight allocation. Secondly, in view of the topological structure construction for affine formation maneuver, a directed
| [1] |
DONG X W, HU G Q. Time-varying formation control for general linear multi-agent systems with switching directed topologies[J]. Automatica, 2016, 73: 47-55. doi: 10.1016/j.automatica.2016.06.024
|
| [2] |
LIN Z Y, DING W, YAN G F, et al. Leader–follower formation via complex Laplacian[J]. Automatica, 2013, 49(6): 1900-1906. doi: 10.1016/j.automatica.2013.02.055
|
| [3] |
LIN Z Y, WANG L L, CHEN Z Y, et al. Necessary and sufficient graphical conditions for affine formation control[J]. IEEE Transactions on Automatic Control, 2015, 61(10): 2877-2891.
|
| [4] |
HAN Z M, WANG L L, LIN Z Y, et al. Formation control with size scaling via a complex Laplacian-based approach[J]. IEEE Transactions on Cybernetics, 2016, 46(10): 2348-2359. doi: 10.1109/TCYB.2015.2477107
|
| [5] |
FANG X, LI X L, XIE L H. Distributed formation maneuver control of multiagent systems over directed graphs[J]. IEEE Transactions on Cybernetics, 2022, 52(8): 8201-8212. doi: 10.1109/TCYB.2020.3044581
|
| [6] |
ZHAO S Y. Affine formation maneuver control of multiagent systems[J]. IEEE Transactions on Automatic Control, 2018, 63(12): 4140-4155. doi: 10.1109/TAC.2018.2798805
|
| [7] |
XU Y, ZHAO S Y, LUO D L, et al. Affine formation maneuver control of high-order multi-agent systems over directed networks[J]. Automatica, 2020, 118: 109004. doi: 10.1016/j.automatica.2020.109004
|
| [8] |
XU Y, LUO D L, YOU Y C, et al. Affine transformation based formation maneuvering for discrete-time directed networked systems[J]. Science China Technological Sciences, 2020, 63(1): 73-85. doi: 10.1007/s11431-018-9456-0
|
| [9] |
CHEN L M, MEI J, LI C J, et al. Distributed leader–follower affine formation maneuver control for high-order multiagent systems[J]. IEEE Transactions on Automatic Control, 2020, 65(11): 4941-4948. doi: 10.1109/TAC.2020.2986684
|
| [10] |
XU Y, LUO D L, LI D Y, et al. Affine formation control for heterogeneous multi-agent systems with directed interaction networks[J]. Neurocomputing, 2019, 330: 104-115. doi: 10.1016/j.neucom.2018.11.023
|
| [11] |
XU Y, LUO D L, LI D Y, et al. Target-enclosing affine formation control of two-layer networked spacecraft with collision avoidance[J]. Chinese Journal of Aeronautics, 2019, 32(12): 2679-2693. doi: 10.1016/j.cja.2019.04.016
|
| [12] |
XU Y, LI D Y, LUO D L, et al. Affine formation maneuver tracking control of multiple second-order agents with time-varying delays[J]. Science China Technological Sciences, 2019, 62(4): 665-676. doi: 10.1007/s11431-018-9328-2
|
| [13] |
LUO Z X, ZHANG P Y, DING X J, et al. Adaptive affine formation maneuver control of second-order multi-agent systems with disturbances[C]// 2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV). Piscataway: IEEE Press, 2020: 1071-1076.
|
| [14] |
CHANG Z Z, WANG J J, LI Z K. Fully distributed event-triggered affine formation maneuver control over directed graphs[J]. IFAC-PapersOnLine, 2022, 55(3): 178-183. doi: 10.1016/j.ifacol.2022.05.031
|
| [15] |
YANG Q K, CAO M, FANG H, et al. Constructing universally rigid tensegrity frameworks with application in multiagent formation control[J]. IEEE Transactions on Automatic Control, 2018, 64(1): 381-388.
|
| [16] |
XIAO F, YANG Q K, ZHAO X Y, et al. A framework for optimized topology design and leader selection in affine formation control[J]. IEEE Robotics and Automation Letters, 2022, 7(4): 8627-8634. doi: 10.1109/LRA.2022.3188883
|
| [17] |
YANG J Y, XIAO F, CHEN T W. Formation tracking of nonholonomic systems on the special euclidean group under fixed and switching topologies: an affine formation strategy[J]. SIAM Journal on Control and Optimization, 2021, 59(4): 2850-2874. doi: 10.1137/20M1328130
|
| [18] |
MONDAL S, TSOURDOS A. Optimal topology for consensus using genetic algorithm[J]. Neurocomputing, 2020, 404: 41-49. doi: 10.1016/j.neucom.2020.04.107
|
| [19] |
崔亚妮, 任佳, 杜文才, 等. 多无人船通信网络拓扑优化控制算法[J]. 控制理论与应用, 2016, 33(12): 1639-1649.
CUI Y N, REN J, DU W C, et al. Network topology optimization control algorithm for multiple unmanned surface vehicle[J]. Control Theory & Applications, 2016, 33(12): 1639-1649(in Chinese).
|
| [20] |
谷晓燕, 陈亮, 邓香平. 无人机编队信息交互拓扑多目标优化[J]. 电光与控制, 2022, 29(9): 27-31,52.
GU X Y, CHEN L, DENG X P. Multi-objective optimization of UAV formation information interaction topology[J]. Electronics Optics & Control, 2022, 29(9): 27-31,52(in Chinese).
|
| [21] |
邦詹森 J, 古廷 G Z. 有向图的理论、算法及其应用[M]. 姚兵, 张忠辅, 译. 北京: 科学出版社, 2009.
BANG-JENSEN J, GUTIN G Z. Digraphs theory, algorithms and applications[M]. YAO B, ZHANG Z F translated. Beijing: Science Press, 2009(in Chinese).
|
| [22] |
HONG H, KIM B J, CHOI M Y, et al. Factors that predict better synchronizability on complex networks[J]. Physical Review E, Statistical, Nonlinear, and Soft Matter Physics, 2004, 69(6 Pt 2): 067105.
|
| [23] |
岳彩通, 梁静, 瞿博阳, 等. 多模态多目标优化综述[J]. 控制与决策, 2021, 36(11): 2577-2588.
YUE C T, LIANG J, QU B Y, et al. A survey on multimodal multiobjective optimization[J]. Control and Decision, 2021, 36(11): 2577-2588(in Chinese).
|
| [24] |
DEB K, PRATAP A, AGARWAL S, et al. A fast and elitist multiobjective genetic algorithm: NSGA-II[J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182-197. doi: 10.1109/4235.996017
|
| [25] |
DEB K, JAIN H. An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: solving problems with box constraints[J]. IEEE Transactions on Evolutionary Computation, 2013, 18(4): 577-601.
|
| [26] |
DENG W, ZHANG X X, ZHOU Y Q, et al. An enhanced fast non-dominated solution sorting genetic algorithm for multi-objective problems[J]. Information Sciences, 2022, 585: 441-453. doi: 10.1016/j.ins.2021.11.052
|
| [27] |
ZHOU A M, ZHANG Q F, JIN Y C. Approximating the set of Pareto-optimal solutions in both the decision and objective spaces by an estimation of distribution algorithm[J]. IEEE Transactions on Evolutionary Computation, 2009, 13(5): 1167-1189. doi: 10.1109/TEVC.2009.2021467
|