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具有传感器增益退化、传输时延和丢包的离线状态估计器

赵国荣 韩旭 王康

赵国荣, 韩旭, 王康. 具有传感器增益退化、传输时延和丢包的离线状态估计器. 自动化学报, 2020, 46(3): 540-548. doi: 10.16383/j.aas.2018.c180230
引用本文: 赵国荣, 韩旭, 王康. 具有传感器增益退化、传输时延和丢包的离线状态估计器. 自动化学报, 2020, 46(3): 540-548. doi: 10.16383/j.aas.2018.c180230
ZHAO Guo-Rong, HAN Xu, WANG Kang. An Ofi-line State Estimator With Sensor Gain Degradation, Transmission Delays and Data Dropouts. ACTA AUTOMATICA SINICA, 2020, 46(3): 540-548. doi: 10.16383/j.aas.2018.c180230
Citation: ZHAO Guo-Rong, HAN Xu, WANG Kang. An Ofi-line State Estimator With Sensor Gain Degradation, Transmission Delays and Data Dropouts. ACTA AUTOMATICA SINICA, 2020, 46(3): 540-548. doi: 10.16383/j.aas.2018.c180230

具有传感器增益退化、传输时延和丢包的离线状态估计器

doi: 10.16383/j.aas.2018.c180230
基金项目: 

国家自然科学基金 61473306

详细信息
    作者简介:

    赵国荣  海军航空大学教授. 1996年获得哈尔滨工业大学控制科学与工程博士学位.主要研究方向为无线传感器网络, 飞行器导航, 制导与控制.E-mail: grzhao6881@163.com

    王康  海军航空大学博士研究生. 2015年获得海军航空大学控制科学与工程硕士学位.主要研究方向为飞行器导航, 制导与控制, 故障检测. E-mail: kycore@163.com

    通讯作者:

    韩旭  海军航空大学博士研究生. 2015年获得海军航空大学控制科学与工程硕士学位.主要研究方向为飞行器导航, 多传感器信息融合.本文通信作者.E-mail: hxyy713@163.com

An Ofi-line State Estimator With Sensor Gain Degradation, Transmission Delays and Data Dropouts

Funds: 

National Natural Science Foundation of China 61473306

More Information
    Author Bio:

    ZHAO Guo-Rong Professor at the Naval Aviation University. He received his Ph. D. degree in control science and engineering from Harbin Institute of Technology in 1996. His research interest covers wireless sensor networks, aircraft navigation, and guidance and control

    HAN Xu Ph. D. candidate at the Naval Aviation University. He received his master degree from Naval Aviation University in 2015. His research interest covers aircraft navigation and multi-sensor information fusion. Corresponding author of this paper

    Corresponding author: WANG Kang Ph. D. candidate at the Naval Aviation University. He received his master degree from Naval Aviation University in 2015. His research interest covers aircraft navigation, guidance and control, and fault detection
  • 摘要: 研究了具有传感器增益退化、数据传输时延和丢包的网络化状态估计问题, 传感器增益退化现象通过统计特性已知的随机变量来描述, 数据包时延和丢失发生于传感器量测输出向远程处理中心传送过程中, 将各时延的发生描述为随机过程, 在远程处理中心端建立只存储最新时刻数据包的时延-丢包模型, 考虑到利用每一时刻实时的时延值和丢包情况, 设计了一种离线的无偏估计器, 推导出最小方差原则下的离线最优估计器增益.最后, 通过算例仿真验证所设计离线状态估计器的有效性.
    Recommended by Associate Editor DONG Hai-Rong
    1)  本文责任编委 董海荣
  • 图  1  网络化状态估计结构图

    Fig.  1  Networked state estimation

    图  2  状态真值与状态估计值的轨迹

    Fig.  2  Trajectories of true state and state estimates

    图  3  两种估计器下的估计误差对比

    Fig.  3  Comparison of two type of estimators

    表  1  退化系数分布在不同区间下的估计稳态误差

    Table  1  Steady-state error with different distribution interval of the degradation coefficient

    $ Df $ tr$ (P_{k} ) $
    $ [0.6, 0.8] $ 0.0708
    $ [0.3, 0.5] $ 0.0939
    $ [0.1, 0.3] $ 0.1341
    下载: 导出CSV

    表  2  乘性噪声分布在不同区间下的估计稳态误差

    Table  2  Steady-state error with different distribution interval of the multiplicative noise

    $ Dg $ tr$ (P_{k} ) $
    $ [-0.1, 0.1] $ 0.0708
    $ [-0.3, 0.3] $ 0.0768
    $ [-0.5, 0.5] $ 0.0886
    下载: 导出CSV
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出版历程
  • 收稿日期:  2018-04-19
  • 录用日期:  2018-08-23
  • 刊出日期:  2020-03-30

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