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有限时间一致无迹Kalman滤波器

刘鹏 田玉平 张亚

刘鹏, 田玉平, 张亚. 有限时间一致无迹Kalman滤波器. 自动化学报, 2020, 46(7): 1357-1366. doi: 10.16383/j.aas.2018.c170726
引用本文: 刘鹏, 田玉平, 张亚. 有限时间一致无迹Kalman滤波器. 自动化学报, 2020, 46(7): 1357-1366. doi: 10.16383/j.aas.2018.c170726
LIU Peng, TIAN Yu-Ping, ZHANG Ya. Finite-time Consensus Based Unscented Kalman Filter. ACTA AUTOMATICA SINICA, 2020, 46(7): 1357-1366. doi: 10.16383/j.aas.2018.c170726
Citation: LIU Peng, TIAN Yu-Ping, ZHANG Ya. Finite-time Consensus Based Unscented Kalman Filter. ACTA AUTOMATICA SINICA, 2020, 46(7): 1357-1366. doi: 10.16383/j.aas.2018.c170726

有限时间一致无迹Kalman滤波器

doi: 10.16383/j.aas.2018.c170726
基金项目: 

国家自然科学基金 61573105

国家自然科学基金 61473081

江苏省自然科学基金 BK20141341

详细信息
    作者简介:

    刘鹏  东南大学自动化学院博士研究生. 2006年获得河南工业大学理学院学士学位, 2011年获得温州大学数学与信息科学学院硕士学位.主要研究方向为多智能体系统, 结构系统, 分布式估计. E-mail: PengLiu_SEU@163.com

    张亚  东南大学自动化学院副教授.主要研究方向为多智能体系统, 分布式滤波理论. E-mail: yazhang@seu.edu.cn

    通讯作者:

    田玉平  东南大学自动化学院教授.主要研究方向为多智能体系统, 通信网络中的优化与控制.本文通信作者. E-mail: yptian@seu.edu.cn

Finite-time Consensus Based Unscented Kalman Filter

Funds: 

National Natural Science Foundation of China 61573105

National Natural Science Foundation of China 61473081

Natural Science Foundation of Jiangsu Province BK20141341

More Information
    Author Bio:

    LIU Peng  Ph. D. candidate at the School of Automation, Southeast University. He received his bachelor degree from the College of Science, Henan University of Technology in 2006, and his master degree from the School of Mathematics and Information Science, Wenzhou University in 2011. His research interest covers the multi-agent systems, structural systems, and distributed estimate

    ZHANG Ya Associate professor at the School of Automation, Southeast University. Her research interest covers the multi-agent systems and distributed filtering theory

    Corresponding author: TIAN Yu-Ping Professor at the School of Automation, Southeast University. His research interest covers the multi-agent systems and optimization and control in communication networks. Corresponding author of this paper
  • 摘要: 本文研究多个传感器测量非线性系统时的分布式无迹Kalman滤波器(Unscented Kalman filter, UKF)的设计问题.借助离散多智能体系统有限时间平均一致算法的思想, 针对无向通信和有向通信网络分别设计了两种不同的滤波算法.对于无向连通的通信拓扑, 利用节点存储的一致性算法的迭代值构造差向量, 由该差向量构成的Hankel矩阵的核来得到分布式无迹Kalman滤波器, 并通过利用误差协方差矩阵的逆来构造Lyapunov函数, 基于随机稳定性引理证明了该有限时间一致无迹Kalman滤波器的稳定性.对于有向强连通的通信拓扑, 结合比率一致和Hankal矩阵的核来设计分布式无迹Kalman滤波器, 该滤波器的稳定性与无向通信拓扑的滤波器相同.最后, 通过仿真例子来验证所提滤波器的跟踪效果.
    Recommended by Associate Editor ZHU Bing
    1)  本文责任编委 诸兵
  • 图  1  6个传感器构成的无向与有向通信图

    Fig.  1  Undirected and directed communication topologies of 6 sensors

    图  2  $6$个节点的平均跟踪偏差

    Fig.  2  The average tracking deviation of $6$ sensors

    图  3  $6$个节点均方估计误差的平均值

    Fig.  3  The mean value of $6$ sensors$'$ mean square estimation error

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出版历程
  • 收稿日期:  2017-12-25
  • 录用日期:  2018-04-04
  • 刊出日期:  2020-07-24

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