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基于黎曼度量的一类反馈控制系统性能监测与诊断

李琳琳 李莎莎 DINGSteven Xianchun 彭鑫 彭开香

李琳琳, 李莎莎, DINGSteven Xianchun, 彭鑫, 彭开香. 基于黎曼度量的一类反馈控制系统性能监测与诊断. 自动化学报, 2021, x(x): 1−13 doi: 10.16383/j.aas.c210027
引用本文: 李琳琳, 李莎莎, DINGSteven Xianchun, 彭鑫, 彭开香. 基于黎曼度量的一类反馈控制系统性能监测与诊断. 自动化学报, 2021, x(x): 1−13 doi: 10.16383/j.aas.c210027
Li Lin-Lin, Li Sha-Sha, Ding Steven Xianchun, Peng Xin, Peng Kai-Xiang. Riemannian metric based performance monitoring and diagnosis for a class of feedback control systems. Acta Automatica Sinica, 2021, x(x): 1−13 doi: 10.16383/j.aas.c210027
Citation: Li Lin-Lin, Li Sha-Sha, Ding Steven Xianchun, Peng Xin, Peng Kai-Xiang. Riemannian metric based performance monitoring and diagnosis for a class of feedback control systems. Acta Automatica Sinica, 2021, x(x): 1−13 doi: 10.16383/j.aas.c210027

基于黎曼度量的一类反馈控制系统性能监测与诊断

doi: 10.16383/j.aas.c210027
基金项目: 国家自然科学基金(62073029, 61873024, 62003140), 北京市自然科学基金(4202045), 中央高校基本业务费(FRF-TP-20-012A3)资助
详细信息
    作者简介:

    李琳琳:北京科技大学自动化学院副教授. 2008年获得西安交通大学学士学位, 2011年获得北京大学硕士学位, 2015 年获得德国杜伊斯堡- 埃森大学博士学位. 主要研究方向为故障诊断与容错控制、智能控制、非线性系统的模糊控制和诊断. E-mail: linlin.li@ustb.edu.cn

    李莎莎:北京科技大学自动化学院硕士研究生. 主要研究方向为故障诊断. E-mail: S20190578@xs.ustb.edu.cn

    DINGSteven Xianchun:德国杜伊斯堡-埃森大学控制工程教授, 自动控制与复杂系统研究所所长. 1992年于德国杜伊斯堡的Gerhard-Mercato大学获得博士学位. 主要研究方向为基于模型与数据驱动的故障诊断、容错控制, 以及其在汽车系统和化工过程中的应用. E-mail: steven.ding@uni-due.de

    彭鑫:华东理工大学能源化工过程智能制造教育部重点实验室研究员. 2009年和2017年分别获得华东理工大学控制科学与工程学士及博士学位. 主要研究方向为工业过程智能建模、控制及优化, 数据驱动的状态监测与溯源诊断. Email: xinpeng@ecust.edu.cn

    彭开香:北京科技大学自动化学院教授, 2007 年获得北京科技大学控制科学与工程博士学位. 主要研究方向为复杂工业系统故障诊断与容错控制. E-mail: kaixiang@ustb.edu.cn

Riemannian Metric Based Performance Monitoring and Diagnosis for a class of Feedback Control Systems

Funds: Supported by National Natural Science Foundation of China (62073029, 61873024, 62003140), Beijing Natural Science Foundation (4202045), the Fundamental Research Funds for the Central Universities (FRF-TP-20-012A3)
More Information
    Author Bio:

    LI Lin-Lin Associate professor in the School of Automation and Electrical Engineering, University of Science and Technology Beijing. She received her B.E. degree from Xi'an Jiaotong University, China, in 2008 and her M.E. degree from Peking University, China, in 2011. In 2015, she received her Ph.D. degree in the Institute for Automatic Control and Complex Systems (AKS), University of Duisburg-Essen, Germany. Her research interests include fault diagnosis and fault tolerant control, intelligent control, fuzzy control and estimation for nonlinear systems

    LI Sha-Sha Master student at the School of Automation and Electrical Engineering, University of Science and Technology Beijing. Her research interest covers fault diagnosis

    DING Steven Xianchun Professor of control engineering and the head of the Institute for Automatic Control and Complex Systems (AKS) at the University of Duisburg-Essen, Germany. He received Ph.D. degree in electrical engineering from the Gerhard-Mercator University of Duisburg, Germany, in 1992. His research interests are model-based and data-driven fault diagnosis, fault tolerant systems, and their application in industry with a focus on automotive systems and chemical processes

    PENG Xin Assistant professor in Key laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, in East China University of Science and Technology, Shanghai, China. He receive his bachelor and Ph.D degree from this university in 2009 and 2017 respectively. His current research interests include modeling, optimization and control of complex industrial process, and data-driven process monitoring and traceable diagnosis

    PENG Kai-Xiang Professor at the School of Automation and Electrical Engineering, University of Science and Technology Beijing. He received his Ph. D. degree in control science and engineering from University of Science and Technology Beijing in 2007. His research interest covers fault diagnosis and fault-tolerant control for complex industrial system

  • 摘要: 针对复杂工业系统对性能衰退的容忍度低等问题, 提出基于系统性能预测的一类反馈控制系统过程监测方法, 通过黎曼度量对控制性能衰退程度进行预测与监测, 并给出发生故障的类型, 以提升过程监测系统的实时性与准确性. 首先, 利用系统的实时数据, 计算系统性能衰退的预测指标; 其次, 利用黎曼度量对系统性能衰退程度进行预测与监测, 并利用随机算法给出对应的阈值来诊断系统性能衰退; 最后, 通过训练各类引发系统性能衰退的故障的性能预测指标集合的中心和阈值, 实现故障的实时定位. 所提出的方法通过三容水箱仿真实验平台进行验证.
  • 图  1  基于黎曼度量的变化检测

    Fig.  1  Riemannian metric based change detection

    图  2  基于黎曼度量的控制性能监测流程图

    Fig.  2  Flow chart of Riemannian metric based control performance monitoring

    图  3  三容水箱示意图

    Fig.  3  The schematic of the three-tank system

    图  4  管道1发生堵塞时诊断效果图

    Fig.  4  Detection of plugging in pipe 1

    图  5  管道2发生堵塞时诊断效果图

    Fig.  5  Detection of plugging in pipe 2

    图  6  管道3发生堵塞时诊断效果图

    Fig.  6  Detection of plugging in pipe 3

    图  7  控制参数不匹配时诊断效果图

    Fig.  7  Detection of controller parameter unmatch

    图  8  基于ISPD的性能检测结果[16]

    Fig.  8  ISPD based performance detection results [16]

    表  1  水箱DTS200的参数

    Table  1  Parameters of tank DTS200

    参数 符号 单位
    水箱面积 $ {\cal{A}} $ 154 $ \mathrm{cm}^{2} $
    水箱间管道面积 $ s_{\mathrm{n}} $ 0.5 $ \mathrm{cm}^{2} $
    水箱最高水位 $ H_{\mathrm{max}} $ 62 $ \mathrm{cm} $
    泵1的最大进水量 $ Q_{1_{\mathrm{max}}} $ 120 $ \mathrm{cm}^{3}/\mathrm{s} $
    泵2的最大进水量 $ Q_{2_{\mathrm{max}}} $ 120 $ \mathrm{cm}^{3}/\mathrm{s} $
    管道1水流系数 $ a_{1} $ 0.45
    管道2水流系数 $ a_{2} $ 0.6
    管道3水流系数 $ a_{3} $ 0.45
    下载: 导出CSV

    表  2  水箱堵塞故障隔离

    Table  2  Isolation of pipe plugging

    故障 $ d_R^2({ P},{ P}_{z,1}) $ $ d_R^2({ P},{ P}_{z,2}) $ $ d_R^2({ P},{ P}_{z,3}) $ 故障隔离
    $ a_1 = 0.3 $ $ 0.0388 $ $ 0.1088 $ $ 0.1193 $ 故障簇1
    $ a_2 = 0.35 $ $ 0.0894 $ $ 0.0270 $ $ 0.0810 $ 故障簇2
    $ a_3 = 0.28 $ $ 0.1258 $ $ 0.1099 $ $ 0.0478 $ 故障簇3
    $ a_1 = 0.27 $ $ 0.0636 $ $ 0.1325 $ $ 0.1409 $ 故障簇1
    $ a_2 = 0.4 $ $ 0.0809 $ $ 0.0139 $ $ 0.0732 $ 故障簇2
    下载: 导出CSV
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