| 引用本文: | 何翌,郑荣濠,张森林,刘妹琴.基于多个自主水下航行器的分布式协同流场估计[J].控制理论与应用,2022,39(11):2036~2045.[点击复制] |
| HE Yi,ZHENG Rong-hao,Zhang Sen-lin,LIU Mei-qin.Distributed cooperative flow field estimation using multiple AUVs[J].Control Theory and Technology,2022,39(11):2036~2045.[点击复制] |
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| 基于多个自主水下航行器的分布式协同流场估计 |
| Distributed cooperative flow field estimation using multiple AUVs |
| 摘要点击 861 全文点击 243 投稿时间：2021-11-05 修订日期：2021-12-30 |
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| DOI编号 10.7641/CTA.2022.11071 |
| 2022,39(11):2036-2045 |
| 中文关键词 流场估计 树型结构 自主式水下航行器 分布式算法 非线性Kaczmarz |
| 英文关键词 flow field estimation tree structure autonomous underwater vehicle distributed algorithm nonlinear Kaczmarz |
| 基金项目 国家自然科学基金委员会–浙江两化融合联合基金(U1709203, U1909206, U1809212), 浙江省自然科学基金(LZ19F030002), 国家自然科学基金 项目(61873235), 浙江省重点研发计划项目(2019C03109)资助. |
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| 中文摘要 |
| 本文考虑利用多个自主式水下航行器(AUV)实现流场估计, 提出了一种基于树型网络的分布式方法来估计
水下流场. 在本文中, 借助绝对运动积分误差和相对运动积分误差, 流场估计问题被描述为求解一个以未知流场为
变元的非线性方程组. 继而本文在多AUV系统内建立一个低通讯成本的树型网络, 并在该网络上运行一种分布式
算法以求解与流场估计相关的非线性方程组. 在该算法中, 每个AUV将当前的流场估计值连续地投影到自身拥有
的约束方程的解集中, 并通过扩散和池化两个步骤在树型网络间传递流场估计值. 本文证明了上述算法的收敛性,
并通过仿真实验验证了所述分布式协同流场估计方法的有效性. |
| 英文摘要 |
| This paper considers the use of multiple autonomous underwater vehicles (AUVs) to estimate the flow field,
and proposes a distributed method based on a tree-structure network to estimate the underwater flow field. In this paper, the
flow field estimation problem is described as solving a nonlinear equation system with the unknown flow field as argument
using absolute motion-integration error and relative motion-integration error. Then this paper establishes a tree-structure
network with low communication cost in the multi-AUV system to run a distributed algorithm to solve the nonlinear
equation system related to the flow field estimation. In this algorithm, each AUV continuously projects current flow field
estimation value to the solution set of its own constraint equations. And through the two steps of dispersion and pooling,
the flow field estimation value is transferred within the tree-structure network. This paper proves the convergence of the
proposed algorithm, and the effectiveness of the distributed cooperative flow field estimation method is verified through
simulation experiments. |
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