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基于迭代学习的线性不确定重复系统间歇性故障估计

冯莉 柴毅 许水清 张可 杨志敏

冯莉, 柴毅, 许水清, 张可, 杨志敏. 基于迭代学习的线性不确定重复系统间歇性故障估计. 自动化学报, 2020, 46(2): 307-319. doi: 10.16383/j.aas.2018.c170252
引用本文: 冯莉, 柴毅, 许水清, 张可, 杨志敏. 基于迭代学习的线性不确定重复系统间歇性故障估计. 自动化学报, 2020, 46(2): 307-319. doi: 10.16383/j.aas.2018.c170252
FENG Li, CHAI Yi, XU Shui-Qing, ZHANG Ke, YANG Zhi-Min. Iterative Learning Based Intermittent Fault Estimation for a Class of Linear Uncertain Repeated Systems. ACTA AUTOMATICA SINICA, 2020, 46(2): 307-319. doi: 10.16383/j.aas.2018.c170252
Citation: FENG Li, CHAI Yi, XU Shui-Qing, ZHANG Ke, YANG Zhi-Min. Iterative Learning Based Intermittent Fault Estimation for a Class of Linear Uncertain Repeated Systems. ACTA AUTOMATICA SINICA, 2020, 46(2): 307-319. doi: 10.16383/j.aas.2018.c170252

基于迭代学习的线性不确定重复系统间歇性故障估计

doi: 10.16383/j.aas.2018.c170252
基金项目: 

国家自然科学基金 61374135

国家自然科学基金 61633005

国家自然科学基金 61673076

国家自然科学基金 61803055

国家自然科学基金 61803140

和重庆市教委科学技术研究项目 KJQN201800720

详细信息
    作者简介:

    冯莉  重庆交通大学交通运输学院讲师. 2017年获得重庆大学自动化学院控制理论与控制工程系博士学位.主要研究方向为故障诊断与故障估计. E-mail: fengli_cqu@126.com

    许水清  合肥工业大学电气与自动化工程学院讲师. 2017年获得重庆大学控制理论与控制工程系博士学位.主要研究方向为信号处理, 故障诊断与故障估计. E-mail:xsqanhui91@gmail.com

    张可   重庆大学自动化学院教授. 2010年获得重庆大学控制理论与控制工程系博士学位.主要研究方向为故障诊断与故障估计. E-mail: smeta@163.com

    杨志敏   重庆大学自动化学院博士研究生.主要研究方向为故障诊断. E-mail: zmyoung@yeah.net

    通讯作者:

    柴毅  重庆大学自动化学院教授. 2001年获得重庆大学自动化学院控制理论与控制工程系博士学位.主要研究方向为信息处理, 融合与控制, 计算机网络与系统控制.本文通信作者. E-mail: chaiyi@cqu.edu.cn

Iterative Learning Based Intermittent Fault Estimation for a Class of Linear Uncertain Repeated Systems

Funds: 

National Natural Science Foundation of China 61374135

National Natural Science Foundation of China 61633005

National Natural Science Foundation of China 61673076

National Natural Science Foundation of China 61803055

National Natural Science Foundation of China 61803140

the Science and Technology Research Program of Chongqing Municipal Education Commission KJQN201800720

More Information
    Author Bio:

    FENG Li    Lecturer at the College of Traffic and Transportation, Chongqing Jiaotong University. She received her Ph.D. degree from Chongqing University in 2017. Her research interest covers fault diagnosis and fault estimation

    XU Shui-Qing   Lecturer at the College of Electrical and Automation Engineering, Hefei University of Technology. He received his Ph. D. degree from Chongqing University in 2017. His research interest covers signal processing, fault diagnosis and fault estimation

    ZHANG Ke    Professor at the College of Automation, Chongqing University. He received his Ph.D. degree from Chongqing University in 2010. His research interest covers fault diagnosis and fault estimation

    YANG Zhi-Min    Ph.D. candidate at the College of Automation, Chongqing University. His main research interest is fault diagnosis

    Corresponding author: CHAI Yi   Professor at the College of Automation, Chongqing University. He received his Ph.D. degree from Chongqing University in 2001. His research interest covers information processing, integration and control, computer network and system control. Corresponding author of this paper
  • 摘要: 针对一类带有不确定参数项的线性重复系统间歇性故障估计问题, 本文提出一种基于迭代学习的故障估计算法.该算法通过设计基于迭代学习的故障估计器和状态观测器, 构造李雅普诺夫方程和优化函数证明该算法的鲁棒性和收敛性, 并通过线性矩阵不等式, 求解出算法中的观测器增益矩阵和迭代学习参数矩阵.区别于其他观测器方法, 本文中的方法利用上一次基于迭代学习观测器输出和系统实际输出产生的残差信号, 对本次的故障信号进行跟踪估计, 从而准确地估计出故障的幅值和形状.仿真结果说明了该算法的有效性和准确性.
    Recommended by Associate Editor WANG Zhan-Shan
    1)  本文责任编委 王占山
  • 图  1  第20次迭代的系统间歇性故障信号及基于迭代学习的故障估计跟踪轨迹

    Fig.  1  The tracking trajectory of intermittent fault for linear system with time-varying parameter uncertainties

    图  2  不同迭代次数系统的间歇性故障估计曲线

    Fig.  2  Intermittent fault estimate result with different iterative index

    图  3  基于迭代学习的间歇性故障估计最大迭代误差

    Fig.  3  The iterative error of intermittent fault for linear system with time-varying parameter uncertainties

    图  4  不同增益矩阵参数$g(k)$的变化趋势

    Fig.  4  The change trend of different gain matrices parameters

    图  5  不同情况下的最大迭代误差变化趋势

    Fig.  5  The change trend of iterative error in different cases

    图  6  基于自适应观测器的时变故障估计

    Fig.  6  The adaptive observer based time-varying fault estimating result

    图  7  基于自适应观测器的时变故障估计误差结果

    Fig.  7  The adaptive observer based time-varying fault estimation error

    图  8  基于迭代学习的时变故障估计结果

    Fig.  8  The iterative learning scheme based time-varying fault estimation result

    图  9  时变故障估计误差结果对比

    Fig.  9  The comparison of time-varying fault estimation error

    图  10  基于自适应观测器的间歇性故障估计结果

    Fig.  10  The adaptive observer based intermittent fault estimation result

    图  11  基于自适应观测器的间歇性故障估计误差结果

    Fig.  11  The adaptive observer based intermittent fault estimation error

    图  12  基于迭代学习的间歇性故障估计结果

    Fig.  12  The iterative learning scheme based intermittent fault estimation result

    图  13  间歇性故障估计误差结果对比

    Fig.  13  The comparison of intermittent fault estimation error

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  • 收稿日期:  2017-06-05
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