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云控制系统不确定性分析与控制器设计方法

关守平 王梁

关守平, 王梁. 云控制系统不确定性分析与控制器设计方法. 自动化学报, 2022, 48(11): 2677−2687 doi: 10.16383/j.aas.c190529
引用本文: 关守平, 王梁. 云控制系统不确定性分析与控制器设计方法. 自动化学报, 2022, 48(11): 2677−2687 doi: 10.16383/j.aas.c190529
Guan Shou-Ping, Wang Liang. Uncertainty analysis of cloud control system with its controller design. Acta Automatica Sinica, 2022, 48(11): 2677−2687 doi: 10.16383/j.aas.c190529
Citation: Guan Shou-Ping, Wang Liang. Uncertainty analysis of cloud control system with its controller design. Acta Automatica Sinica, 2022, 48(11): 2677−2687 doi: 10.16383/j.aas.c190529

云控制系统不确定性分析与控制器设计方法

doi: 10.16383/j.aas.c190529
基金项目: 国家自然科学基金(62173072) 资助
详细信息
    作者简介:

    关守平:东北大学信息科学与工程学院教授. 1995年获得东北大学工业自动化系博士学位. 主要研究方向为复杂工业过程建模, 优化与控制, 网络与云控制, 智能控制. E-mail: guanshouping@ise.neu.edu.cn

    王梁:北京航空航天大学自动化科学与电气工程学院博士研究生. 2019年获得东北大学信息科学与工程学院自动化系学士学位. 主要研究方向为飞行器控制, 网络与云控制. 本文通信作者.E-mail: wang_liang@buaa.edu.cn

Uncertainty Analysis of Cloud Control System With Its Controller Design

Funds: Supported by National Natural Science Foundation of China (62173072)
More Information
    Author Bio:

    GUAN Shou-Ping Professor at the College of Information Science and Engineering, Northeastern University. He received his Ph.D. degree from the Department of Industrial Automation, Northeastern University in 1995. His research interest covers industrial process modeling, optimization and control, networked and clouded control, and intelligent control

    WANG Liang Ph.D. candidate at the School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics. He received his bachelor degree from the College of Information Science and Engineering, Northeastern University in 2019. His research interest covers aircraft control, networked and clouded control. Corresponding author of this paper

  • 摘要: 云控制系统(Cloud control system, CCS)是云计算与物理系统的融合, 由于云计算中资源是动态的, 因此云计算的加入使得云控制系统具有很大的不确定性. 本文给出一种典型的云控制系统结构, 通过将不确定性划分为云端不确定性和网络端不确定性, 有效简化了云控制系统不确定特性分析和建模. 针对典型的时延不确定性问题, 将云控制系统时延划分为云端时延和网络端时延, 进行了MapReduce模型下多计算节点云端时延分析, 同时进行了云控制结构下网络端时延分析, 两者结合实现了云控制系统的前向通道和反馈通道的时延建模. 基于所建立的云控制系统时延模型, 应用极点配置方法设计了云控制器算法, 包括观测器的设计和控制律的设计, 从而保证了闭环系统的稳定性. 对本文设计的云控制器算法进行了仿真验证, 结果表明考虑时延特性的控制器设计明显提升了云控制系统的控制性能.
  • 图  1  常规控制系统结构

    Fig.  1  The structure of conventional control system

    图  2  云控制系统结构

    Fig.  2  The structure of CCS

    图  3  云控制系统实现结构

    Fig.  3  The realization structure of CCS

    图  4  云控制系统理论结构模型

    Fig.  4  The theoretical structural model of CCS

    图  5  云控制系统不确定性分解图

    Fig.  5  The uncertainty division diagrgam of CCS

    图  6  MapReduce任务执行架构

    Fig.  6  The task execution architecture under MapReduce

    图  7  云端基于MapReduce任务执行模型

    Fig.  7  The task execution model under MapReduce in the cloud-end

    图  8  一般网络传输时延组成图

    Fig.  8  The delay composition graph of general network transmission

    图  9  云控制系统网络端传输时延组成图

    Fig.  9  The delay composition graph of the network-end in the CCS

    图  10  云控制系统时延模型结构

    Fig.  10  The structure of CCS time-delay model

    图  11  带有控制器的云控制系统结构

    Fig.  11  The structure of CCS with controller

    图  12  云特性影响控制效果对比图

    Fig.  12  The contrast graph of cloud characteristics influencing control effect

    图  13  短时延云特性控制器控制效果对比图

    Fig.  13  Contrast graph of control effect of short time-delay cloud characteristic controller

    图  14  长时延云特性控制器控制效果对比图

    Fig.  14  Contrast graph of control effect of long time-delay cloud characteristic controller

    表  1  愿意节点列表

    Table  1  The list of willing modes

    节点 IP 地址 优先级 排序
    $C_{1}$ $Add_{1}$ $S_{1}$ 1
    $C_{2}$ $Add_{2}$ $S_{1}$ 2
    $\vdots $ $\vdots $ $\vdots $ $\vdots $
    $C_{g}$ $Add_{g}$ $S_{g}$ $g$
    $\vdots $ $\vdots $ $\vdots $ $\vdots $
    $C_{M}$ $Add_{M}$ $S_{M}$ $M$
    下载: 导出CSV
  • [1] 游科友, 谢立华. 网络控制系统的最新研究综述. 自动化学报, 2013, 39(2): 101-118

    You Ke-you, Xie Li-hua. Survey of Recent Progress in Networked Control Systems. Acta Automatica Sinica, 2013, 39(2): 101-118
    [2] Xia Y. From networked control systems to cloud control systems. In: Proceedings of the 2012 Control Conference. Beijing, China: IEEE, 2012. 5878−5883
    [3] Schlechtendahl J, Kretschmer F, Sang Z, et al. Extended study of network capability for cloud based control systems. Robotics & Computer Integrated Manufacturing, 2017, 43: 89-95
    [4] Chinacloud: The concept and connotation of cloud computing [Online], available: http://www.chinacloud.cn/show.aspxid=14668&cid=17, March 3, 2019
    [5] 李伯虎, 柴旭东, 张霖, 林廷宇. 智慧云制造: 工业云的智造模式和手段. 中国工业评论, 2016(2): 58-66

    Li Bo-hu, Chai Xu-dong, Zhang Lin, Lin Ting-yu. Smart cloud manufacturing: intelligent manufacturing model and means of industrial cloud. China Industry Review, 2016(Z1): 56-66
    [6] 罗军舟, 金嘉晖, 宋爱波, 东方. 计算: 体系架构与关键技术. 通信学报, 2011 37(2): 3-21

    Luo Jun-zhou, Jin Jia-hui, Song Ai-bo, Dong Fang. Cloud computing: architecture and key technologies. Journal on Communications, 2011 37(2): 3-21
    [7] Hayes B. Cloud computing. Communications of the ACM, 2008 51(7): 9-11 doi: 10.1145/1364782.1364786
    [8] 夏元清. 云控制系统及其面临的挑战. 自动化学报, 2016, 42(1): 1-12

    Xia Yuan-qing. Cloud Control Systems and Their Challenges. Acta Automatica Sinica, 2016, 42(1): 1-12
    [9] Xia Y, Qin Y, Zhai D H, et al. Further results on cloud control systems. Science China Information Sciences, 2016 59(7): 232-236
    [10] 夏元清, 闫策, 王笑京, 宋向辉. 智能交通信息物理融合云控制系统. 自动化学报, 2019, 45(01): 132-142

    Xia Yuan-qing, Yan Ce, Wang Xiao-jing, Song Xiang-hui. Intelligent Transportation Cyber-physical Cloud Control Systems. Acta Automatica Sinica, 2019, 45(01): 132-142
    [11] Wu Hai-yan, Lou Lei, Chih-Chung Chen, Sandra Hirche, and Kolja Kühnlenz. Cloud-based networked visual servo control. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2013, 60(2): 554-566 doi: 10.1109/TIE.2012.2186775
    [12] Jan Schlechtendahl, Felix Kretschmer, Zhiqian Sang, Armin Lechler, Xun Xu. Extended study of network capability for cloud based control systems. Robotics and Computer-Integrated Manufacturing, 2017, 43: 89-95 doi: 10.1016/j.rcim.2015.10.012
    [13] Ding Qing, Cao Si-tan. A Cloud-Based Learning Tool for Graduate Software Engineering Practice Courses With Remote Tutor Support. IEEE Access, 2017, 5: 2262-2271 doi: 10.1109/ACCESS.2017.2664070
    [14] Le Xu, Huang Di-jiang. Cloud-Based Virtual Laboratory for Network Security Education. IEEE TRANSACTIONS ON EDUCATION, 2014, 57(3): 145-150 doi: 10.1109/TE.2013.2282285
    [15] Ma L, Xia Y Q, Ali Y, Zhan Y F. Engineering problems in initial phase of cloud control system. In: Proceedings of the 36th Chinese Control Conference. Dalian, China: IEEE, 2017. 7892−7896
    [16] 王飞跃, 王成红. 基于网络控制的若干基本问题的思考和分析. 自动化学报, 2002, 28(Z): 171-176

    Wang Fei-yue, Wang Cheng-hong. On Some Basic Issues in Network-Based Direct Control Systems. Acta Automatica Sinica, 2002, 28(Z): 171-176
    [17] 王剑平, 张云生, 张果, 张晶. 并行分布控制网络的实时信号时序流图分析. 控制与决策, 2010, 25(11): 1727-1731

    Wang Jian-ping, Zhang Yun-sheng, Zhang Guo, Zhang Jing. Analysis of signal timing sequence flow chart on parallel and distribute control network. Control and Decision, 2010, 25(11): 1727-1731
    [18] 唐晓铭, 邓梨, 虞继敏, 屈洪春. 基于区间二型T-S模糊模型的网络控制系统的输出反馈预测控制. 自动化学报, 2019, 45(3): 604-616

    Tang Xiao-ming, Deng Li, Yu Ji-min, Qu Hong-chun. Output feedback model predictive control for interval type-2 T-S fuzzy networked control systems. Acta Automatica Sinica, 2019, 45(3): 604-616
    [19] Cloosterman M B G, Wouw N V D, Heemels W P M H, et al. Stability of Networked Control Systems With Uncertain Time-Varying Delays. IEEE Transactions on Automatic Control, 2009, 54(7): 1575-1580 doi: 10.1109/TAC.2009.2015543
    [20] 王彩璐, 陶跃钢, 杨鹏, 刘作军, 周颖. 云控制系统并行任务分配优化算法与并联控制. 自动化学报,2017, 43(11): 1973-1983

    Wang Cai-lu, Tao Yue-gang, Yang Peng, Liu Zuo-jun, Zhou Ying. Parallel Task Assignment Optimization Algorithm and Parallel Control for Cloud Control Systems. Acta Automatica Sinica, 2017, 43(11): 1973-1983
    [21] M Malekimajd, D Ardagna, M Ciavotta, E Gianniti, M Passacantando, A M Rizzi. An optimization framework for the capacity allocation and admission control of MapReduce jobs in cloud systems. The Journal of Supercomputing, 2018, 74(10): 5314-5348 doi: 10.1007/s11227-018-2426-2
    [22] 李建江, 崔健, 王聃, 严林, 黄义双. MapReduce并行编程模型研究综述. 电子学报, 2011, 39(11): 2635-2642

    Li Jian-jiang, Cui Jian, Wang Dan, Yan Lin,Huang Yi-shuang. Survey of MapReduce Parallel Programming Model. Acta Automatica Sinica, 2011, 39(11): 2635-2642
    [23] Xia Yuan-qing. Cloud Control Systems. Acta Automatica Sinica, 2015, 2(02): 134-142 Acta Automatica Sinica doi: 10.1109/JAS.2015.7081652
    [24] 关守平, 周玮, 尤富强. 网络控制系统与应用. 北京: 电子工业出版社, 2008. 15−18

    Guan Shou-Ping, Zhou Wei, You Fu-Qiang. Networked Control Systems and Applications. Beijing: Publishing House of Electronics Industry, 2008. 15−18
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出版历程
  • 收稿日期:  2019-07-15
  • 录用日期:  2019-10-11
  • 网络出版日期:  2022-08-08
  • 刊出日期:  2022-11-22

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