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多智能体仿射编队机动控制的有向交互拓扑优化设计

马苏慧 张栋 王孟阳 王庭晖 刘送丹

马苏慧,张栋,王孟阳,等. 多智能体仿射编队机动控制的有向交互拓扑优化设计[J]. 北京航空航天大学学报,2025,51(4):1367-1376 doi: 10.13700/j.bh.1001-5965.2023.0180
引用本文: 马苏慧,张栋,王孟阳,等. 多智能体仿射编队机动控制的有向交互拓扑优化设计[J]. 北京航空航天大学学报,2025,51(4):1367-1376 doi: 10.13700/j.bh.1001-5965.2023.0180
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
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

多智能体仿射编队机动控制的有向交互拓扑优化设计

doi: 10.13700/j.bh.1001-5965.2023.0180
基金项目: 国家自然科学基金(61933010)
详细信息
    通讯作者:

    E-mail:zhangdong@nwpu.edu.cn

  • 中图分类号: TP273;N945.15

Directed interactive topology optimization design for multi-agent affine formation maneuver control

Funds: National Natural Science Foundation of China (61933010)
More Information
  • 摘要:

    研究了多智能体仿射编队机动控制的有向交互拓扑优化设计问题。考虑信息交互成本、信息传播能耗等优化指标,建立了包含拓扑结构构造和权重配置的仿射编队机动有向拓扑优化模型;针对仿射编队机动拓扑结构构造,提出了有向k根图的检测方法,实现了有向信息交互拓扑的d+1根约束求解,并设计了一种改进NSGA-II的拓扑结构构造优化算法,以二维空间中7个智能体的编队为例进行仿真验证,结果表明:改进NSGA-II的拓扑结构构造优化算法具有更好的优化效果,能够有效地为仿射编队机动控制提供多种可行的有向交互拓扑,并且所生成的交互拓扑能够满足有向d+1根图的要求。

     

  • 图 1  表1对应的拓扑结构

    Figure 1.  Topology structure corresponding to Table 1

    图 2  编队轨迹

    Figure 2.  Formation trajectory

    图 3  总编队误差范数

    Figure 3.  Total formation error norm

    表  1  拓扑结构构造结果

    Table  1.   Topology structure construction results

    拓扑编号$ {f_1} $$ {f_2} $${f_3}$${f_4}$
    ${{\mathcal{G}}_1}$1243.556.001.25
    ${{\mathcal{G}}_2}$1243.554.831.50
    ${{\mathcal{G}}_3}$1244.214.001.25
    ${{\mathcal{G}}_4}$1244.693.501.50
    ${{\mathcal{G}}_5}$1244.934.001.00
    ${{\mathcal{G}}_6}$1245.202.501.75
    ${{\mathcal{G}}_7}$1246.152.002.00.
    ${{\mathcal{G}}_8}$1348.733.331.50
    ${{\mathcal{G}}_9}$1350.151.832.00
    ${{\mathcal{G}}_{10}}$1350.811.672.00
    ${{\mathcal{G}}_{11}}$1352.001.002.50
    ${{\mathcal{G}}_{12}}$1352.001.502.25
    ${{\mathcal{G}}_{13}}$1447.743.501.00
    ${{\mathcal{G}}_{14}}$1453.632.331.75
    ${{\mathcal{G}}_{15}}$1453.872.501.50
    ${{\mathcal{G}}_{16}}$1454.811.332.25
    ${{\mathcal{G}}_{17}}$1456.471.172.25
    ${{\mathcal{G}}_{18}}$1458.320.502.75
    ${{\mathcal{G}}_{19}}$1459.850.003.00
    ${{\mathcal{G}}_{20}}$1553.403.001.25
    ${{\mathcal{G}}_{21}}$1560.000.332.75
    ${{\mathcal{G}}_{22}}$1560.470.832.50
    ${{\mathcal{G}}_{23}}$1562.470.672.50
    ${{\mathcal{G}}_{24}}$1659.052.001.50
    ${{\mathcal{G}}_{25}}$1868.001.831.75
    ${{\mathcal{G}}_{26}}$1868.001.831.75
    ${{\mathcal{G}}_{27}}$2075.481.332.00
    ${{\mathcal{G}}_{28}}$2077.141.002.00
    下载: 导出CSV

    表  2  算法评估指标结果

    Table  2.   Algorithm evaluation indicator results

    算法 ${N_{{\text{PS}}}}$
    平均值
    ${N_{{\text{PSMF}}}}$
    平均值
    IGDX IGDF 暴力
    搜索
    平均值 方差 平均值 方差
    imNSGA-II 2.15 0.05 3.1857 4.9742 3.7809 423.7237 37
    本文 23.16 0.58 2.3401 3.4508 1.3760 5.8359 15
    下载: 导出CSV
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出版历程
  • 收稿日期:  2023-04-14
  • 录用日期:  2023-08-10
  • 网络出版日期:  2023-09-05
  • 整期出版日期:  2025-04-30

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