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基于广义PI观测器零点配置的抗扰残差评估和故障检测

胡宇翔 代学武 崔东亮 周冬

胡宇翔, 代学武, 崔东亮, 周冬. 基于广义PI观测器零点配置的抗扰残差评估和故障检测. 自动化学报, 2022, 45(x): 1−14 doi: 10.16383/j.aas.c211235
引用本文: 胡宇翔, 代学武, 崔东亮, 周冬. 基于广义PI观测器零点配置的抗扰残差评估和故障检测. 自动化学报, 2022, 45(x): 1−14 doi: 10.16383/j.aas.c211235
Hu Yu-Xiang, Dai Xue-Wu, Cui Dong-Liang, Zhou Dong. A generalized proportional-integral observer with zero assignment for disturbance rejection residual evaluation and fault detection. Acta Automatica Sinica, 2022, 45(x): 1−14 doi: 10.16383/j.aas.c211235
Citation: Hu Yu-Xiang, Dai Xue-Wu, Cui Dong-Liang, Zhou Dong. A generalized proportional-integral observer with zero assignment for disturbance rejection residual evaluation and fault detection. Acta Automatica Sinica, 2022, 45(x): 1−14 doi: 10.16383/j.aas.c211235

基于广义PI观测器零点配置的抗扰残差评估和故障检测

doi: 10.16383/j.aas.c211235
基金项目: 国家自然科学基金 (61773111, 61790574), 黑龙江省“百千万”工程科技重大专项 (2020ZX03A02)资助
详细信息
    作者简介:

    胡宇翔:东北大学流程工业综合自动化国家重点实验室博士. 2020年获得沈阳建筑大学学士学位. 主要研究方向为鲁棒故障检测和容错控制. E-mail: HuYx0126@163.com

    代学武:东北大学流程工业综合自动化国家重点实验室教授. 主要研究方向为鲁棒状态估计和状态监测, 多智能体系统的同步, 网络化控制与智能调度协同优化及其在工业物联网高精度时间同步, 轨道交通调度控制一体化等领域的应用. 本文通信作者. E-mail: daixuewu@mail.neu.edu.cn

    崔东亮:东北大学流程工业综合自动化国家重点实验室讲师. 分别于1999年、2001年获得华中科技大学学士学位和硕士学位, 2013年获得东北大学博士学位. 主要研究方向为工业互联网与人工智能. E-mail: cuidongliang@mail.neu.edu.cn

    周冬:齐重数控装备股份有限公司电气工程师. 主要研究方向为数控机床和检测技术. E-mail: 13763512779@163.com

A Generalized Proportional-integral Observer With Zero Assignment for Disturbance Rejection Residual Evaluation and Fault Detection

Funds: Supported by National Natural Science Foundation of China (61773111, 61790574), Key Science and Technology Project of Heilongjiang Province (2020ZX03A02)
More Information
    Author Bio:

    HU Yu-Xiang Ph.D. candidate at the State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University. He received his bachelor degree from Shenyang Jianzhu University in 2020. His research interest covers robust fault detection and fault-tolerant control

    DAI Xue-Wu Professor at the State Key Laboratory of Synthetical Automation for Process Industries at Northeastern University. His research interest covers robust state estimation and condition monitoring of industrial systems, networked scheduling and control, wireless sensor actuator networks, applications to Industrial Internet of things and railway train rescheduling. Corresponding author of this paper

    CUI Dong-Liang Lecturer at the State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University. He received his bachelor and master degrees from Huazhong University of Science and Technology in 1999 and 2001, and received his Ph.D. degree from Northeastern University in 2013. His research interest covers Industrial Internet of things and Artificial Intelligence

    ZHOU Dong Electrical engineer at Qiqihar Heavy Computer Numerical Control Equipment Company Limited. His research interest covers computer numerical control machine and detection technology

  • 摘要: 针对一类存在周期性扰动的系统, 提出了一种新型的基于广义PI观测器零点配置的抗扰残差评估框架, 充分利用了广义PI观测器的零点可配置性, 通过调整传递函数矩阵在阻塞零点处的相位响应并利用该频点处矩阵的零特征向量对残差信号进行滤波, 实现了残差信号与周期性扰动的解耦. 此外, 还创新性地提出了一种基于矩阵条件数的优化目标函数, 改善了残差信号对故障的敏感性. 最后, 通过两轮自平衡小车的仿真对比实验和实物测试, 验证了所提方法在残差抑扰和故障检测方面的有效性.
  • 图  1  基于广义PI观测器和残差评估的故障检测系统框图

    Fig.  1  Block diagram of a fault detection system based on a generalized PI observer and residual evaluation section

    图  2  传递函数矩阵相位调整和抗扰滤波原理示意图

    Fig.  2  Concept illustration of the proposed phase adjustment of disturbance transfer function matrix for disturbance rejection

    图  3  比例观测器的输出残差信号的1024-FFT频谱

    Fig.  3  Spectrum of the residual from a proportional observer by 1024-FFT

    图  4  无故障时残差信号对比图

    Fig.  4  Comparison of the residuals in fault-free scenario

    图  5  无故障时残差信号的1024-FFT对比图

    Fig.  5  Comparison of the 1024-FFT spectrum of the residuals in fault-free scenario

    图  6  发生渐变式故障时残差信号对比图

    Fig.  6  Comparison of the residuals under the ramp fault

    图  7  发生较小的渐变式故障时残差信号对比图

    Fig.  7  Comparison of the residuals under the smaller ramp fault

    图  8  发生突发式故障时残差信号对比图

    Fig.  8  Comparison of the residuals under the abrupt fault

    图  9  实物测试残差信号对比图

    Fig.  9  Comparison of the residuals from physical tests

    表  1  残差特征和安全阈值对比

    Table  1  Comparison of residual characteristics and safety thresholds

    检测方法 均值$E\left(\tilde{r}_{k}\right)$ 标准差$\delta\left(\tilde{r}_{k}\right)$安全阈值$\pm 3\delta$
    P观测器 −0.060 6.949 [−20.91, 20.79]
    PI观测器 −1.229 5.268 [−17.03, 14,58]
    广义PI观测器 −0.694 1.510 [−5.22, 3.84]
    广义PI观测器+实
    系数增益向量
    −0.003 0.075 [−0.23, 0.22]
    下载: 导出CSV
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  • 收稿日期:  2021-12-27
  • 录用日期:  2022-04-07
  • 网络出版日期:  2022-05-31

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