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高动态协同拓扑在线优化与分布式制导方法

庞博文 朱建文 包为民 李小平

韦 艺, 康 锐, 程海龙等 . 军用飞机再次出动准备时间计算方法[J]. 北京航空航天大学学报, 2008, 34(12): 1415-1418.
引用本文: 庞博文,朱建文,包为民,等. 高动态协同拓扑在线优化与分布式制导方法[J]. 北京航空航天大学学报,2025,51(1):333-339 doi: 10.13700/j.bh.1001-5965.2022.1025
Wei Yi, Kang Rui, Cheng Hailonget al. Calculation method for military aircraft’s turnaround time[J]. Journal of Beijing University of Aeronautics and Astronautics, 2008, 34(12): 1415-1418. (in Chinese)
Citation: PANG B W,ZHU J W,BAO W M,et al. High dynamic cooperative topology online optimization and distributed guidance method[J]. Journal of Beijing University of Aeronautics and Astronautics,2025,51(1):333-339 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.1025

高动态协同拓扑在线优化与分布式制导方法

doi: 10.13700/j.bh.1001-5965.2022.1025
基金项目: 国家自然科学基金(62173336)
详细信息
    通讯作者:

    E-mail:zhujianwen1117@163.com

  • 中图分类号: V243.1;TJ765.3

High dynamic cooperative topology online optimization and distributed guidance method

Funds: National Natural Science Foundation of China (62173336)
More Information
  • 摘要:

    针对高速飞行器集群飞行过程中的分布式协同制导问题,提出了基于最小生成树的自适应拓扑优化与制导方法。构建了飞行器集群通信链路的拓扑图,根据通信代价将距离量化为权值,通过最小生成树中Kruskal算法思想实时生成最优通信拓扑图;采用分布式双层协同制导构架与多中心分布式拓扑优化决策方法,在一致性协同控制律中对协调变量进行补偿计算;实现了飞行器集群协同飞行中的拓扑自适应优化调控。仿真验证结果表明了所提方法的有效性与优异性能。

     

  • 图 1  协同飞行自适应拓扑优化结构流程

    Figure 1.  Flow chart of adaptive topology optimization structure for cooperative flight

    图 2  通信链路拓扑构建示意图

    Figure 2.  Schematic diagram of communication link topology construction

    图 3  最小生成树示意图

    Figure 3.  Schematic diagram of minimum spanning tree

    图 4  协同飞行拓扑优化算法示意图

    Figure 4.  Schematic diagram of cooperative flight topology optimization algorithm

    图 5  协同飞行状态信息

    Figure 5.  Cooperative flight status information

    图 6  3个中心协同飞行过程拓扑结构变化

    Figure 6.  Topological structure changes during cooperative flight of three center

    表  1  仿真条件设置

    Table  1.   Simulation condition setting

    飞行器 初始纬度/(°) 初始经度/(°) 终端方位角/(°) 机动幅值
    1 10.01 99.98 −95 0.1
    2 10.00 99.98 −94 0.2
    3 9.99 99.98 −93 0.3
    4 10.01 99.99 −92 0.4
    5 10.00 99.99 −91 0.5
    6 9.99 99.99 −90 0.1
    7 10.01 100.00 −89 0.2
    8 10.00 100.00 −88 0.3
    9 9.99 100.00 −87 0.4
    10 10.00 100.01 −86 0.5
    下载: 导出CSV
  • [1] 陈新庄, 郭志伟, 李江荣. 一阶一致性收敛速率的拓扑优化方法综述[J]. 延安大学学报(自然科学版), 2022, 41(2): 42-51.

    CHEN X Z, GUO Z W, LI J R. An overview of topology optimization for improving the convergence rate of first-order consensus protocols[J]. Journal of Yanan University (Natural Science Edition), 2022, 41(2): 42-51(in Chinese).
    [2] 杨彦祥. 无人机集群拓扑构型关键技术研究[D]. 成都: 电子科技大学, 2022.

    YANG Y X. Research on key technologies of UAV cluster topology configuration[D]. Chengdu: University of Electronic Science and Technology of China, 2022(in Chinese).
    [3] 马丹, 张宝峰, 王璐瑶. 多智能体系统一致性问题的控制器与拓扑协同优化设计[J]. 控制理论与应用, 2019, 36(5): 720-727. doi: 10.7641/CTA.2018.70950

    MA D, ZHANG B F, WANG L Y. Controller and topology co-optimization for consensus of multi-agent systems[J]. Control Theory & Applications, 2019, 36(5): 720-727(in Chinese). doi: 10.7641/CTA.2018.70950
    [4] REN W. Consensus strategies for cooperative control of vehicle formations[J]. IET Control Theory & Applications, 2007, 1(2): 505-512.
    [5] GIULIETTI F, POLLINI L, INNOCENTI M. Autonomous formation flight[J]. IEEE Control Systems Magazine, 2000, 20(6): 34-44. doi: 10.1109/37.887447
    [6] 董文奇, 何锋. 大规模 UAV编队信息交互拓扑的分级分布式生成[J]. 航空学报, 2021, 42(6): 452-462.

    DONG W Q, HE F. Hierarchical and distributed generation of information interaction topology for large scale UAV formation[J]. Acta Aeronautica et AstronauticaSinica, 2021, 42(6): 452-462(in Chinese).
    [7] 冉华明, 熊蓉玲. 空战中机群编队分层优化算法[J]. 航空学报, 2020, 41(S2): 44-52.

    RAN H M, XIONG R L. Hierarchical optimization algorithm for air fleet formation in air-combat[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41(S2): 44-52(in Chinese).
    [8] 罗小元, 杨帆, 李绍宝, 等. 多智能体系统的最优持久编队生成策略[J]. 自动化学报, 2014, 40(7): 1311-1319.

    LUO X Y, YANG F, LI S B, et al. Generation of optimally persistent formation for multi-agent systems[J]. Acta Automatica Sinica, 2014, 40(7): 1311-1319(in Chinese).
    [9] WANG G Q, LUO H, HU X X. Generation of optimal persistent formations for heterogeneous multi-agent systems with a leader constraint[J]. Chinese Physics B, 2018, 27(2): 028901. doi: 10.1088/1674-1056/27/2/028901
    [10] WANG G Q, LUO H, HU X X, et al. Communication topology optimization for three-dimensional persistent formation with leader constraint[J]. Optimization Letters, 2021, 15(2): 513-535. doi: 10.1007/s11590-018-1308-0
    [11] 罗贺, 李晓多, 王国强. 能耗均衡的三维最优持久编队通信拓扑生成[J]. 航空学报, 2022, 43(1): 514-531. doi: 10.7527/j.issn.1000-6893.2022.1.hkxb202201039

    LUO H, LI X D, WANG G Q. Energy-balanced communication topology generation of three-dimensional optimally persistent formation[J]. Acta Aeronautica et Astronautica Sinica, 2022, 43(1): 514-531(in Chinese). doi: 10.7527/j.issn.1000-6893.2022.1.hkxb202201039
    [12] 徐星光, 王晓峰, 姚璐, 等. 固定翼无人机编队构型与通信拓扑优化[J]. 系统工程与电子技术, 2022, 44(9): 2936-2946. doi: 10.12305/j.issn.1001-506X.2022.09.29

    XU X G, WANG X F, YAO L, et al. Formation configuration and communication topology optimization for fixed-wing UAVs[J]. Systems Engineering and Electronics, 2022, 44(9): 2936-2946(in Chinese). doi: 10.12305/j.issn.1001-506X.2022.09.29
    [13] 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. doi: 10.7641/CTA.2016.60473

    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). doi: 10.7641/CTA.2016.60473
    [14] QU G N, LI N. Accelerated distributed nesterov gradient descent[J]. IEEE Transactions on Automatic Control, 2020, 65(6): 2566-2581. doi: 10.1109/TAC.2019.2937496
    [15] 庞博文, 朱建文, 包为民, 等. 通信长时间中断的分布式自主协同制导策略[J]. 战术导弹技术, 2022(4): 69-77.

    PANG B W, ZHU J W, BAO W M, et al. Distributed autonomous cooperative guidance strategy for long time communication interruption[J]. Tactical Missile Technology, 2022(4): 69-77(in Chinese).
    [16] BONDY J A, MURTY U S R. Graph theory[M]. London: Springer London, 2008.
    [17] ZHU J W, LIU L H, TANG G J, et al. Optimal guidance with multi-targets for hypersonic vehicle in dive phase[C]// 2013 6th International Conference on Recent Advances in Space Technologies (RAST). Piscataway: IEEE Press, 2013: 341-346.
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出版历程
  • 收稿日期:  2022-12-31
  • 录用日期:  2023-03-04
  • 网络出版日期:  2023-04-06
  • 整期出版日期:  2025-01-31

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