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不同通信定位方式下AUV编队智能控制方法综述

俞建成 陈阔 张进

俞建成, 陈阔, 张进. 不同通信定位方式下AUV编队智能控制方法综述[J]. 水下无人系统学报, 2023, 31(1): 30-37 doi: 10.11993/j.issn.2096-3920.2022-0079
引用本文: 俞建成, 陈阔, 张进. 不同通信定位方式下AUV编队智能控制方法综述[J]. 水下无人系统学报, 2023, 31(1): 30-37 doi: 10.11993/j.issn.2096-3920.2022-0079
YU Jian-cheng, CHEN Kuo, ZHANG Jin. Intelligent Control Method for AUV Formation under Different Communication and Positioning Methods: A Review[J]. Journal of Unmanned Undersea Systems, 2023, 31(1): 30-37. doi: 10.11993/j.issn.2096-3920.2022-0079
Citation: YU Jian-cheng, CHEN Kuo, ZHANG Jin. Intelligent Control Method for AUV Formation under Different Communication and Positioning Methods: A Review[J]. Journal of Unmanned Undersea Systems, 2023, 31(1): 30-37. doi: 10.11993/j.issn.2096-3920.2022-0079

不同通信定位方式下AUV编队智能控制方法综述

doi: 10.11993/j.issn.2096-3920.2022-0079
基金项目: 国家自然科学基金资助(62273340, 51909257); 辽宁省自然科学基金资助(2021-MS-031)
详细信息
    作者简介:

    俞建成(1976-), 男, 研究员, 博导, 主要研究方向为水下机器人系统、控制方法及自主观测理论等

    通讯作者:

    张 进(1987-), 男, 副研究员, 硕导, 主要研究方向为海洋机器人建模与控制

  • 中图分类号: TJ630.33; TP242

Intelligent Control Method for AUV Formation under Different Communication and Positioning Methods: A Review

  • 摘要: 综述了国内外自主水下航行器(AUV)在光学和声学2种不同通信定位方式下的编队智能控制方法。首先, 归纳了AUV编队的基础模型, 这些模型是考虑通信定位约束时智能控制方法设计的基础。其次, 针对光学与声学2种通信定位方式, 归纳了考虑通信定位约束时的技术难点和智能控制方法, 并对研究成果进行了总结。最后, 对AUV编队智能控制的发展趋势进行了分析和探讨。可为AUV编队智能控制方法的设计提供参考, 对AUV编队的理论研究和工程化应用具有借鉴意义。

     

  • 图  1  领航-跟随者法示意图

    Figure  1.  Diagram of the leader-follower method

    图  2  虚拟结构法示意图

    Figure  2.  Diagram of virtual structure method

    图  3  水下光学定位场景特征

    Figure  3.  Characteristics of underwater optical positioning scene

    图  4  AUV编队通信定位时间延迟示意图

    Figure  4.  Diagram of time delay for AUV formation communication and positioning

    图  5  AUV编队通信定位中断示意图

    Figure  5.  Diagram of AUV formation communication and positioning interruption

    表  1  AUV编队智能控制总结

    Table  1.   Summary of intelligent control of AUV formation

    文献通信定位方式编队应用场景问题特征使用方法验证形式试验成果
    [13] 光学通信定位 水下充电和信息交互、区域残骸探测、石油管道同步监测、珊瑚礁同步监测等 相对位姿难以准确测量 高斯拉普拉斯算子算法 2台AUV在湖中进行队形变换(对接)试验 最大的位置误差为9.818 mm
    [14] 相对位姿难以准确测量 卡尔曼滤波法 2台AUV在水池中进行队形变换(对接)试验 纵向位置误差趋于0 mm
    [16] 个体之间易碰撞 智能优化分配方法 在仿真环境中, 6台AUV在3 m的区域内作队形变换 无碰撞运动
    [17] 个体之间易碰撞 Lennard-Jones势能法 保持队形的6条机器鱼在水箱中实现了半径为357 mm的同相位差圆周运动 无碰撞运动
    [24~29] 声学通信定位 海底调查和测绘、资源勘探、水下考古勘探、水下救援等 时延信息可以获得 状态反馈法 在仿真环境中, 6台AUV在0.5 s的控制周期下进行队形保持和变换 系统可容忍0.4 s通信定位时延
    [30] 时延信息可以获得 鲁棒控制法 在仿真环境中, 4台AUV在0.3 s的控制周期下进行队形保持和变换 系统可容忍0.6 s通信定位时延
    [31] 时延信息可以获得 自适应控制法 在仿真环境中, 5台AUV在0.2 s的控制周期下进行队形保持和变换 系统可容忍5 s通信定位时延
    [32] 时延信息可以获得 最优控制法 在仿真环境中, 5台AUV在0.2 s的控制周期下进行队形保持和变换 系统可容忍2 s通信定位时延
    [33] 时延信息无法获得 梯度下降法 在水池中, 3台AUV在0.2 s的控制周期下进行队形保持和变换 系统可容忍5 s通信定位时延
    [34] 时延信息无法获得 核密度方法估计法 在湖中, 3台AUV在5 s的控制周期下进行队形保持和变换 系统可容忍4 s通信定位时延
    [34] 通信中断 曲线拟合法 在湖中, 3台AUV在5 s的控制周期下进行队形保持和变换 系统可容忍30%丢包率
    [35] 通信中断 改进的广义预测控制法 在仿真环境中, AUV编队在0.1 s的控制周期下进行队形保持和变换 系统可容忍0.7 s通信定位中断
    [36] 通信中断 改进的视线法 在湖中, 2台AUV在20 s的控制周期下进行队形保持和变换 系统可容忍3%的丢包率
    [37] 通信中断 滑模控制器和观测器联合控制 在仿真环境中, 3台AUV在0.1 s的控制周期下进行队形保持和变换 系统可容忍0.6 s通信定位中断
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出版历程
  • 收稿日期:  2022-11-25
  • 修回日期:  2023-01-21
  • 录用日期:  2023-01-31
  • 网络出版日期:  2023-02-06

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