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工业物联网中的精确时钟同步: 网络化控制理论观点

王頲 徐小权 唐晓铭 黄庆卿 李永福

王頲, 徐小权, 唐晓铭, 黄庆卿, 李永福. 工业物联网中的精确时钟同步: 网络化控制理论观点. 自动化学报, 2021, 47(7): 1720-1738 doi: 10.16383/j.aas.c180811
引用本文: 王頲, 徐小权, 唐晓铭, 黄庆卿, 李永福. 工业物联网中的精确时钟同步: 网络化控制理论观点. 自动化学报, 2021, 47(7): 1720-1738 doi: 10.16383/j.aas.c180811
Wang Ting, Xu Xiao-Quan, Tang Xiao-Ming, Huang Qing-Qing, Li Yong-Fu. Precise clock synchronization in industrial internet of things: Networked control perspective. Acta Automatica Sinica, 2021, 47(7): 1720-1738 doi: 10.16383/j.aas.c180811
Citation: Wang Ting, Xu Xiao-Quan, Tang Xiao-Ming, Huang Qing-Qing, Li Yong-Fu. Precise clock synchronization in industrial internet of things: Networked control perspective. Acta Automatica Sinica, 2021, 47(7): 1720-1738 doi: 10.16383/j.aas.c180811

工业物联网中的精确时钟同步: 网络化控制理论观点

doi: 10.16383/j.aas.c180811
基金项目: 

国家自然科学基金 61972061

国家自然科学基金 51605065

国家自然科学基金 61403055

国家自然科学基金 51705059

重庆市教委科学技术研究项目 KJZD-K201900604

重庆市基础研究与前沿探索(重庆市自然科学基金)项目 2017jcyjAX0453

重庆市基础研究与前沿探索(重庆市自然科学基金)项目 cstc2018jcyjAX0139

重庆市基础研究与前沿探索(重庆市自然科学基金)项目 cstc2018jcyjAX0691

重庆市教委项目 KJ1600402

详细信息
    作者简介:

    徐小权  重庆邮电大学先进制造工程学院硕士研究生. 主要研究方向为网络控制, 无线传感器网络, 时钟同步和同步采集. E-mail: jhlee126@126.com

    唐晓铭  重庆邮电大学副教授. 2008年于攀枝花学院信息与工程学院获得学士学位, 2013年于重庆大学自动化学院获得博士学位. 主要研究方向为网络化控制与系统, 预测控制理论与方法. E-mail: tangxm@cqupt.edu.cn

    黄庆卿  重庆邮电大学自动化学院副教授. 2009年和2015年于重庆大学分别获得学士学位和博士学位. 主要研究方向为智能状态监测与故障诊断, 无线传感器网络, 时钟同步采集和机械振动. E-mail: qingq.huang@gmail.com

    李永福  重庆邮电大学自动化学院副教授. 2012年获得重庆大学控制与工程博士学位.主要研究方向为智能网联汽车和空地协同控制. E-mail: laf1212@163.com

    通讯作者:

    王頲   重庆邮电大学先进制造工程学院教授. 2001年于西南交通大学获得机械工程学士学位, 2006年于西南交通大学获得机电工程博士学位. 主要研究方向为物联网理论与应用, 网络化控制理论与应用.本文通信作者. E-mail: wangting@cqupt.edu.cn

Precise Clock Synchronization in Industrial Internet of Things: Networked Control Perspective

Funds: 

National Natural Science Foundation of China 61972061

National Natural Science Foundation of China 51605065

National Natural Science Foundation of China 61403055

National Natural Science Foundation of China 51705059

cience and Technology Research Program of Chongqing Municipal Education Commission KJZD-K201900604

Chongqing Science and Technology Commission 2017jcyjAX0453

Chongqing Science and Technology Commission cstc2018jcyjAX0139

Chongqing Science and Technology Commission cstc2018jcyjAX0691

Chongqing Education Administration Program Foundation of China KJ1600402

More Information
    Author Bio:

    XU Xiao-Quan Master student at the School of Advanced and Manufacturing Engineering, Chongqing University of Posts and Telecommunications. His research interest covers network control, wireless sensor networks, time synchronization, and synchronous acquisition

    TANG Xiao-Ming Associate professor at the School of Automation, Chongqing University of Posts and Telecommunications. He received his bachelor degree from the College of Information and Electrical Engineering, Panzhihua University in 2008 and Ph. D. degree from the College of Automation, Chongqing University in 2013. His research interest covers basic research in networked control and systems, and predictive control theory and method

    HUANG Qing-Qing Associate professor at the School of Automation, Chongqing University of Posts and Telecommunications.He received his bachelor degree and Ph. D. degree, both from Chongqing University in 2009 and 2015, respectively. His research interest covers intelligent condition monitoring and fault diagnosis, wireless sensor networks, clock synchronization acquisition, and mechanical vibration

    LI Yong-Fu Associate professor at the School of Automation, Chongqing University of Posts and Telecommunications. He received his Ph. D. degree in control science and engineering from Chongqing University in 2012. His research interest covers connected and automated vehicles and air-ground cooperative control

    Corresponding author: WANG Ting Professor at the School of Advanced and Manufacturing Engineering, Chongqing University of Posts and Telecommunications. He received his bachelor degree in mechanical engineering in 2001 and Ph. D. degree in mechatronic engineering in 2006, both from Southwest Jiaotong University. His research interest covers internet of things theory and application, and network control theory and application. Corresponding author of this paper
  • 摘要:

    本文针对物联网中时变的时钟参数, 运用网络化控制理论观点, 通过对时钟状态建模的本质分析, 区别于"相对时钟建模", 提出了全分布规模化时钟状态追踪卡尔曼滤波(Kalman filtering). 考虑量测的丢失, 则扩展为追踪时钟参数的修正Kalman filtering算法. 我们提出了以BMU (Basic measurement unit)构建新的MMSE (Minimum mean square error)等价变换下的能观测性状态解耦量测模型, 新的量测模型能够实现MMSE量测规模化扩展, 且理论上分析了时钟同步的条件和计算了统计时钟同步误差的相应上界, 并且在时钟同步精度与潜在的通信网络质量间作出了量化均衡.

  • 图  1  一组时钟信息交换过程($z_{i, k}^{\{i, j\}}$和$z_{j, k}^{\{j, i\}}$互为对称量测信息)

    Fig.  1  A set of clock information exchange processes ($z_{i, k}^{\{i, j\}}$ and $z_{j, k}^{\{j, i\}}$ are symmetrical measurement information each other)

    图  2  可观性对BMU RAMSE系统稳定性的影响

    Fig.  2  Effect of observability for system stability of a BMU-RAMSE

    图  3  可观性对BMU-RMSE系统稳定性的影响

    Fig.  3  Effect of observability for system stability of a BMU-RMSE

    图  4  BMU系统RAMSE估计性能

    Fig.  4  Estimation performance with BMU systems-RAMSE

    图  5  BMU系统RMSE估计性能

    Fig.  5  Estimation performance with BMU systems-RMSE

    图  6  测量的临界接受率—上限

    Fig.  6  Critical acceptance rate of measurement — upper bound

    图  7  Monte Carlo实验

    Fig.  7  Monte Carlo experiment

    表  1  不可靠量测丢包变量定义

    Table  1  Definition of unreliable packet loss variables

    名称 定义
    $\pi_{i, k}^{\{i, j\}}$ 描述$S_i$和$S_j$间第$k$次信息交换. 交换成功, 则$\pi_{i, k}^{\{i, j\}}=1$; 否则$\pi_{i, k}^{\{i, j\}}=0$. 多链路下, $S_i$与任意邻居$S_{m_j}$间则为$\pi_{i, k}^{\{i, m_j\}}$
    $\phi_{i, j}$ 描述$S_i$和$S_j$间的接收概率, $P(\pi_{i, k}^{\{i, j\}}=1)=\phi_{i, j}$, $P(\pi_{i, k}^{\{i, j\}}$ $=0)=1-\phi_{i, j}$. 多链路下, $S_i$与任意邻居$S_{m_j}$间则为$\phi_{i, m_j}$
    $\boldsymbol{\chi}$ 表示一个同步周期, $S_i$与$|\mathcal{N}_i|$个邻居的$|\mathcal{N}_i|$次信息交换中, 丢包组合$\boldsymbol{\chi}=\{\chi_1, \chi_2, \cdots, \chi_g, \cdots, \chi_{2^{|\mathcal{N}_i|}}|g\in \{1$, $2$, $\cdots$, $2^{|\mathcal{N}_i|}\}\}$, $\chi_g$为第$g$种丢包情况, 共$2^{|\mathcal{N}_i|}$种
    $\pi_{i, g, k}^{\{i, m_j\}}$ 描述第$k$个采样周期第$g$种丢包情况时($\chi_g$), $S_i$与$S_{m_j}$信息交换是否成功地取值. 若成功, $\pi_{i, g, k}^{\{i, m_j\}}=1$, 否则$\pi_{i, g, k}^{\{i, m_j\}}$ $=$ $0$
    $\boldsymbol{L}_{i, g, k}$ 如$\pi_{i, g, k}^{\{i, m_j\}}$, 则$\boldsymbol{L}_{i, g, k}={\rm diag}\{\pi_{i, g, k}^{\{i, m_1\}}, \cdots, \pi_{i, g, k}^{\{i, m_j\}}$, $\cdots$, $\pi_{i, g, k}^{\{i, m_{|\mathcal{N}_i|}\}}\}$, 表示$S_i$与所有邻居在$\chi_g$情况时的丢包系数矩阵
    $\eta_{i, g, k}$ 与所有邻居在$\chi_g$时的概率$\eta_{i, g, k}=\prod_{j=1}^{|\mathcal{N}_i|} \alpha_{i, m_j, k}$
    $\alpha_{i, m_j, k}$ 表示$S_i$与$S_{m_j}$信息交换概率
    $\alpha_{i, m_j, k}=\begin{cases} \phi_{i, m_j}, &\mbox{若}~ \pi_{i, k}^{\{i, m_j\}}=1\\ 1-\phi_{i, m_j}, &\mbox{若}~ \pi_{i, k}^{\{i, m_j\}}=0 \end{cases}$
    $\boldsymbol{\gamma}_{i, g, k}$ 第$k$步绝对量测信息$\boldsymbol{\gamma}_{i, k}$在$\chi_g$情况时的具体表达式, $\boldsymbol{\gamma}_{i, g, k}$为构造的值, 实际量测中不可获得
    $\boldsymbol{z}_{i, g}(k)$ 第$k$步相对量测信息$\boldsymbol{z}_{i}(k)$在$\chi_g$情况时的具体表达式, $\boldsymbol{z}_{i, g}(k)$为一个实际中能够量测的值
    下载: 导出CSV
  • [1] 王恒, 陈鹏飞, 王平. 面向WIA-PA工业无线传感器网络的确定性调度算法. 电子学报, 2018, 46(1): 68-74 doi: 10.3969/j.issn.0372-2112.2018.01.010

    Wang Heng, Chen Peng-Fei, Wang Ping. Deterministic scheduling algorithms for WIA-PA industrial wireless sensor networks. Acta Electronica Sinica, 2018, 46(1): 68-74 doi: 10.3969/j.issn.0372-2112.2018.01.010
    [2] Luo B, Wu Y C. Distributed clock parameters tracking in wireless sensor network. IEEE Transactions on Wireless Communications, 2013, 12(12): 6464-6475 doi: 10.1109/TWC.2013.103013.130811
    [3] Wu Y C, Chaudhari Q, Serpedin E. Clock synchronization of wireless sensor networks. IEEE Signal Processing Magazine, 2011, 28(1): 124-138 doi: 10.1109/MSP.2010.938757
    [4] 王頲, 万羊所, 唐晓铭, 黄庆卿, 李永福. 不可靠WSN时钟同步网络化输出反馈MPC量化分析. 仪器仪表学报, 2017, 38(7): 1798 -1808 doi: 10.3969/j.issn.0254-3087.2017.07.029

    Wang Ting, Wan Yang-Suo, Tang Xiao-Ming, Huang Qing-Qing, Li Yong-Fu. Unreliable WSN clock synchronization networked output feedback model predictive control quantitative analysis. Chinese Journal of Scientific Instrument, 2017, 38(7): 1798-1808 doi: 10.3969/j.issn.0254-3087.2017.07.029
    [5] Schenato L, Fiorentin F. Average TimeSynch: A consensus-based protocol for clock synchronization in wireless sensor networks. Automatica, 2011, 47(9): 1878-1886 doi: 10.1016/j.automatica.2011.06.012
    [6] He J P, Cheng P, Shi L, Chen J M, Sun Y X. Time synchronization in WSNs: A maximum-value-based consensus approach. IEEE Transactions on Automatic Control, 2014, 59(3): 660-675 doi: 10.1109/TAC.2013.2286893
    [7] Garone E, Gasparri A, Lamonaca F. Clock synchronization protocol for wireless sensor networks with bounded communication delays. Automatica, 2015, 59: 60-72 doi: 10.1016/j.automatica.2015.06.014
    [8] Bolognani S, Carli R, Lovisari E, Zampieri S. A randomized linear algorithm for clock synchronization in multi-agent systems. IEEE Transactions on Automatic Control, 2016, 61(7): 1711-1726 doi: 10.1109/TAC.2015.2479136
    [9] Sinopoli B, Schenato L, Franceschetti M, Poolla K, Jordan M I, Sastry S S. Kalman filtering with intermittent observations. IEEE Transactions on Automatic Control, 2004, 49(9): 1453-1464 doi: 10.1109/TAC.2004.834121
    [10] Huang M Y, Dey S. Stability of Kalman filtering with Markovian packet losses. Automatica, 2007, 43(4): 598-607 doi: 10.1016/j.automatica.2006.10.023
    [11] Mo Y L, Sinopoli B. A characterization of the critical value for Kalman filtering with intermittent observations. In: Proceedings of the 47th IEEE Conference on Decision and Control. Cancun, Mexico: IEEE, 2008. 2692-2697
    [12] Sinopoli B, Schenato L, Franceschetti M, Poolla K, Jordan M I, Sastry S S. Kalman filtering with intermittent observations. IEEE Transactions on Automatic Control, 2004, 49(9): 1453-1464 doi: 10.1109/TAC.2004.834121
    [13] Plarre K, Bullo F. On Kalman filtering for detectable systems with intermittent observations. IEEE Transactions on Automatic Control, 2009, 54(2): 386-390 doi: 10.1109/TAC.2008.2008347
    [14] You K Y, Fu M Y, Xie L H. Mean square stability for Kalman filtering with Markovian packet losses. Automatica, 2011, 47(12): 2647-2657 doi: 10.1016/j.automatica.2011.09.015
    [15] Deshmukh S, Natarajan B, Pahwa A. State estimation over a lossy network in spatially distributed cyber-physical systems. IEEE Transactions on Signal Processing, 2014, 62(15): 3911-3923 doi: 10.1109/TSP.2014.2330810
    [16] He X, Wang Z D, Wang X F, Zhou D H. Networked strong tracking filtering with multiple packet dropouts: Algorithms and applications. IEEE Transactions on Industrial Electronics, 2014, 61(3): 1454-1463 doi: 10.1109/TIE.2013.2261038
    [17] Hu J, Wang Z D, Gao H J. Recursive filtering with random parameter matrices, multiple fading measurements and correlated noises. Automatica, 2013, 49(11): 3440-3448 doi: 10.1016/j.automatica.2013.08.021
    [18] Hu J, Wang Z D, Gao H J, Stergioulas L K. Extended Kalman filtering with stochastic nonlinearities and multiple missing measurements. Automatica, 2012, 48(9): 2007- 2015 doi: 10.1016/j.automatica.2012.03.027
    [19] Quevedo D E, Ahlen A, Johansson K H. State estimation over sensor networks with correlated wireless fading channels. IEEE Transactions on Automatic Control, 2013, 58(3): 581-593 doi: 10.1109/TAC.2012.2212515
    [20] Wei G L, Wang Z D, Shu H S. Robust filtering with stochastic nonlinearities and multiple missing measurements. Automatica, 2009, 45(3): 836-841 doi: 10.1016/j.automatica.2008.10.028
    [21] Sui T J, You K Y, Fu M Y. Stability conditions for multi-sensor state estimation over a lossy network. Automatica, 2015, 53: 1-9 doi: 10.1016/j.automatica.2014.12.022
    [22] 王頲, 段斯静, 黄庆卿, 唐晓铭, 李永福. 工业物联网确定性调度中TDMA紧时隙时间精度边界可靠性分析. 仪器仪表学报, 2018, 39(6): 120-131 https://www.cnki.com.cn/Article/CJFDTOTAL-YQXB201806016.htm

    Wang Ting, Duan Si-Jing, Huang Qing-Qing, Tang Xiao-Ming, Li Yong-Fu. Reliability analysis of time precision boundary for tight slots of TDMA in deterministic scheduling of industrial internet of things. Chinese Journal of Scientific Instrument, 2018, 39(6): 120-131 https://www.cnki.com.cn/Article/CJFDTOTAL-YQXB201806016.htm
    [23] Li Y, Pan Y, Wang P. Research and implementation of a mobility management mechanism for wireless sensor networks based on IEEE 802.15.4. In: Proceedings of the 2011 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems. Kunming, China: IEEE, 2011. 260-264
    [24] Wang H, Ge G C, Chen J M, Wang P. A reliable routing protocol based on deterministic schedule for wireless industrial networks. In: Proceedings of the 3rd International Conference on Computer Science and Information Technology. Chengdu, China: IEEE, 2010. pp. 368-372
    [25] Watteyne T, Palattella M R, Grieco L A. Using IEEE 802.15.4e Time-Slotted Channel Hopping (TSCH) in the Internet of Things (IoT): Problem Statement. Internet Engineering Task Force, 2015. [Online], available: http://www.rfc-editor.org/info/rfc7554, June 18, 2021
    [26] Wang T, Cai C Y, Guo D, Tang X M, Wang H. Clock synchronization in wireless sensor networks: A new model and analysis approach based on networked control perspective. Mathematical Problems in Engineering, 2014, 2014(3): 1- 19 http://www.researchgate.net/publication/273876748_Clock_Synchronization_in_Wireless_Sensor_Networks_A_New_Model_and_Analysis_Approach_Based_on_Networked_Control_Perspective
    [27] Wang T, Guo D, Cai C Y, Tang X M, Wang H. Clock synchronization in wireless sensor networks: Analysis and design of error precision based on lossy networked control perspective. Mathematical Problems in Engineering, 2015, 2015: Article ID 346521 http://www.researchgate.net/publication/275229110_Clock_Synchronization_in_Wireless_Sensor_Networks_Analysis_and_Design_of_Error_Precision_Based_on_Lossy_Networked_Control_Perspective
    [28] Cao X H, Cheng P, Chen J M, Ge S S, Cheng Y, Sun Y X. Cognitive radio based state estimation in cyber-physical systems. IEEE Journal on Selected Areas in Communications, 2014, 32(3): 489-502 doi: 10.1109/JSAC.2014.1403002
    [29] Kay S M. Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory. Beijing: Publishing House of Electronics Industry, 2014. 307-309
    [30] Elson J, Girod L, Estrin D. Fine-grained network time synchronization using reference broadcasts. ACM SIGOPS Operating Systems Review, 2002, 36(SI): 147-163 doi: 10.1145/844128.844143
    [31] Maybeck P S. Stochastic Models, Estimation, and Control. New York: Academic Press, 1979.
    [32] Ackermann J E. On the synthesis of linear control systems with specified characteristics. Automatica, 1977, 13(1): 89- 94 doi: 10.1016/0005-1098(77)90012-7
    [33] Äström K J, Wittenmark B. Computer-Controlled Systems: Theory and Design. Upper Saddle River, NJ, USA: Prentice Hall, 1997.
    [34] Anderson B D O, Moore J B. Optimal Filtering. Englewood Cliffs, NJ: Prentice Hall, 1979.
    [35] Kucera V. The discrete riccati equation of optimal control. Kybernetica, 1972, 8(5): 430-447 http://www.ams.org/mathscinet-getitem?mr=332254
    [36] 汪付强, 曾鹏, 于海斌. 一种低开销的双向时间同步算法. 仪器仪表学报, 2011, 32(6): 1357-1363 https://www.cnki.com.cn/Article/CJFDTOTAL-YQXB201106023.htm

    Wang Fu-Qiang, Zeng Peng, Yu Hai-Bin. Low overhead two-way time synchronization algorithm. Chinese Journal of Scientific Instrument, 2011, 32(6): 1357-1363 https://www.cnki.com.cn/Article/CJFDTOTAL-YQXB201106023.htm
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  • 收稿日期:  2018-12-05
  • 录用日期:  2019-03-19
  • 刊出日期:  2021-07-01

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