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基于Agent与元胞自动机的无人机集群混合式控制

肖宗豪 张鹏 迟文升 刘畅

肖宗豪, 张鹏, 迟文升, 等 . 基于Agent与元胞自动机的无人机集群混合式控制[J]. 北京航空航天大学学报, 2021, 47(11): 2344-2359. doi: 10.13700/j.bh.1001-5965.2020.0385
引用本文: 肖宗豪, 张鹏, 迟文升, 等 . 基于Agent与元胞自动机的无人机集群混合式控制[J]. 北京航空航天大学学报, 2021, 47(11): 2344-2359. doi: 10.13700/j.bh.1001-5965.2020.0385
XIAO Zonghao, ZHANG Peng, CHI Wensheng, et al. Hybrid control for UAV swarms based on Agent and cellular automata[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(11): 2344-2359. doi: 10.13700/j.bh.1001-5965.2020.0385(in Chinese)
Citation: XIAO Zonghao, ZHANG Peng, CHI Wensheng, et al. Hybrid control for UAV swarms based on Agent and cellular automata[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(11): 2344-2359. doi: 10.13700/j.bh.1001-5965.2020.0385(in Chinese)

基于Agent与元胞自动机的无人机集群混合式控制

doi: 10.13700/j.bh.1001-5965.2020.0385
基金项目: 

国家自然科学基金 61703422

国家自然科学基金 61903378

详细信息
    通讯作者:

    张鹏, E-mail: peng1439@163.com

  • 中图分类号: V249;V279

Hybrid control for UAV swarms based on Agent and cellular automata

Funds: 

National Natural Science Foundation of China 61703422

National Natural Science Foundation of China 61903378

More Information
  • 摘要:

    高效有序的集群控制方式是集群顺利完成作战任务的前提。针对无人机集群控制问题,结合集中式与分布式2种控制方式,提出基于Agent与元胞自动机的集群混合式控制。从无人机集群作战流程出发构建了无人机集群控制体系框架、通信拓扑结构及集群控制规则,将集群个体由上至下分为中心长机、小组长机、个体无人机3个层次,高层级对低层级采用自上而下的集中式控制,同层级采用自下而上的分布式控制。在此基础上,利用Agent模型的层次性与元胞自动机模型的同质性,设计了基于Agent与元胞自动机的集群混合式控制模型,实现2种控制方式有效结合,元胞自动机模型实现集群基本的聚合、分离、速度一致规则,Agent模型实现不同层级个体间的协同交互规则。在编队集结与保持任务背景下,对分布式、集中式与混合式3种控制进行对比仿真,结果表明:基于混合式控制的集群在编队可控性、跟随性、一致性以及降低通信负载等方面具有明显优势,验证了混合式集群控制方法的有效性。

     

  • 图 1  元胞自动机结构示意图

    Figure 1.  Schematic diagram of cellular automata structure

    图 2  Agent结构模型

    Figure 2.  Agent structure model

    图 3  OODA作战环

    Figure 3.  OODA operations ring

    图 4  无人机集群作战流程

    Figure 4.  Flowchart of UAV swarms operations

    图 5  无人机集群混合式控制框架结构

    Figure 5.  Hybrid control framework for UAV swarms

    图 6  无人机集群时变混合式通信拓扑结构

    Figure 6.  Time-varying hybrid communication topology of UAV swarms

    图 7  集群任务分解

    Figure 7.  Swarms task decomposition

    图 8  集群个体自由度变化

    Figure 8.  Change of individual degree of freedom in swarms

    图 9  Agent与元胞自动机混合控制结构

    Figure 9.  Hybrid control structure of Agent and cellular automata

    图 10  Moore型邻域元胞

    Figure 10.  Moore neighborhood cell

    图 11  平滑力函数图像

    Figure 11.  Smooth force function image

    图 12  集群编队状态

    Figure 12.  Swarms formation status

    图 13  三种控制方式集群速度变化曲线

    Figure 13.  Swarms speed variation curves of three control modes

    图 14  三种控制方式编队速度一致性偏差

    Figure 14.  Formation speed consistency deviation of three control modes

    图 15  三种控制方式的集群离散度变化曲线

    Figure 15.  Variation curves of swarms dispersion in three control modes

    图 16  三种控制方式集群通信次数变化曲线

    Figure 16.  Swarms communication frequency variation curves of three control modes

    图 17  三种控制方式单节点最大通信次数

    Figure 17.  Maximum number of single node communications in three control modes

    表  1  仿真参数

    Table  1.   Simulation parameters

    参数 数值 参数 数值
    Vmax/(m·s-1) 100 ω3 1
    umax/(m·s-2) 7 cm1, mMg 0.1
    R0/m 50 cm2, mMg 0.2
    γ 0.1 cm3, mMg 0.1
    h 0.7 cm4, mMg 0.2
    a 1 λ1 1
    b 2 λ2 1
    c1 0.1 λ3 1
    c2 0.2 ci1, iUa 0.1
    θi/(°) 45 ci2, iUa 0.2
    κ 6 ci3, iUa 0.1
    ϕ/(°) 150 ci4, iUa 0.2
    β1 1 b1 0.1
    β2 1 b2 0.1
    co1 0.1 b3 0.1
    co2 0.2 b4 0.1
    ω1 1 b5 0.1
    ω2 1 Vomin/(m·s-1) 60
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-08-04
  • 录用日期:  2020-09-04
  • 网络出版日期:  2021-11-20

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