2.765

2022影响因子

(CJCR)

  • 中文核心
  • EI
  • 中国科技核心
  • Scopus
  • CSCD
  • 英国科学文摘

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于X2统计检验的线性离散时滞系统故障检测

刘博昂 叶昊

刘博昂, 叶昊. 基于X2统计检验的线性离散时滞系统故障检测. 自动化学报, 2014, 40(7): 1278-1284. doi: 10.3724/SP.J.1004.2014.01278
引用本文: 刘博昂, 叶昊. 基于X2统计检验的线性离散时滞系统故障检测. 自动化学报, 2014, 40(7): 1278-1284. doi: 10.3724/SP.J.1004.2014.01278
LIU Bo-Ang, YE Hao. Statistical X2 Testing Based Fault Detection for Linear Discrete Time-delay Systems. ACTA AUTOMATICA SINICA, 2014, 40(7): 1278-1284. doi: 10.3724/SP.J.1004.2014.01278
Citation: LIU Bo-Ang, YE Hao. Statistical X2 Testing Based Fault Detection for Linear Discrete Time-delay Systems. ACTA AUTOMATICA SINICA, 2014, 40(7): 1278-1284. doi: 10.3724/SP.J.1004.2014.01278

基于X2统计检验的线性离散时滞系统故障检测

doi: 10.3724/SP.J.1004.2014.01278
基金项目: 

Supported by National Natural Science Foundation of China (61290324)

Statistical X2 Testing Based Fault Detection for Linear Discrete Time-delay Systems

Funds: 

Supported by National Natural Science Foundation of China (61290324)

More Information
    Corresponding author: YE Hao Professor in the Department ofAutomation, Tsinghua University. He re-ceived his bachelor and Ph.D. degrees inautomation from Tsinghua University, in1992 and 1996, respectively. His researchinterest covers fault detection and diagno-sis of dynamic systems. E-mail:haoye@tsinghua.edu.cn
  • 摘要: 基于X2统计检验,研究了一类含状态时滞线性离散时变系统的故障检测问题. 与基于残差的传统故障检测方法不同, 本文直接应用测量输出构造残差评价函数, 并通过投影与新息分析, 得到了残差评价函数的Riccati递推解. 分析表明, 该方法有效降低了残差评价函数的计算量, 并且在无故障发生情况下服从X2分布. 进一步, 通过X2统计检验可以判断系统是否有故障发生. 最后,通过一算例验证了提出方法的有效性.
  • [1] Chen J, Patton R. Robust Model-based Fault Diagnosis for Dynamic Systems. Boston: Kluwer, 1999. 1-10
    [2] Ding S X. Model-Based Fault Diagnosis Techniques: Design Schemes, Algorithms, and Tools. Berlin: Springer, 2013. 73-85
    [3] Gertler J. Fault Detection and Diagnosis in Engineering Systems. New York: Marcel Dekker, 1998. 363-383
    [4] Hu Chang-Hua, Zhang Qi, Qiao Yu-Kun. A strong tracking particle filter with application to fault prediction. Acta Automatica Sinica, 2008, 34(12): 1522-1528 (in Chinese)
    [5] Zhou Dong-Hua, Hu Yan-Yan. Fault diagnosis techniques for dynamic systems. Acta Automatica Sinica, 2009, 35(6): 748 -758 (in Chinese)
    [6] Hwang I, Kim S, Kim Y, Seah C E. A survey of fault detection, isolation, and reconfiguration methods. IEEE Transactions on Control Systems Technology, 2010, 18(3): 636-653
    [7] Jiang B, Chowdhury F N. Fault estimation and accommodation for linear MIMO discrete-time systems. IEEE Transactions on Control Systems Technology, 2005, 13(3): 493-499
    [8] Zhao C H, Li W Q, Sun Y X, Gao F R. Multiple local reconstruction model-based fault diagnosis for continuous processes. Acta Automatica Sinica, 2013, 39(5): 497-493
    [9] Li Y Y, Zhong M Y. On optimal fault detection for discrete-time Markovian jump linear systems. Acta Automatica Sinica, 2013, 39(6): 926-932
    [10] Chen Ye, Hu Chang-Hua, Zhou Zhi-Jie, Zhang Wei, Wang Hua-Guo. Method of improving square-root center difference Kalman filter with application to incipient failure detection. Acta Automatica Sinica, 2013, 39(10): 1703-1713 (in Chinese)
    [11] He X, Wang Z Z, Liu Y, Zhou D H. Least-squares fault detection and diagnosis for networked sensing systems using a direct state estimation approach. IEEE Transactions on Industrial Informatics, 2013, 9(3): 1670-1679
    [12] Chen J, Patton R J. Standard H∞ filtering formulation of robust fault detection. In: Proceedings of SAFEPROCESS'2000. Budapest, Hungary: IFAC, 2000. 256 -261
    [13] Wan Y M, Dong W, Ye H. Distributed H∞ filtering with consensus strategies in sensor networks: considering consensus tracking error. Acta Automatica Sinica, 2012, 38(7): 1211-1217
    [14] Zhong M Y, Zhou D H, Ding S X. On designing H∞ fault detection filter for linear discrete time-varying systems. IEEE Transactions on Automatic Control, 2010, 55(7): 1689-1695
    [15] Chen L, Zhong M Y, Zhang M Y. H∞ fault detection for linear singular systems with time-varying delay. International Journal of Control, Automation, and Systems, 2011, 9(1): 9 -14
    [16] Zhong M, Liu S, Zhao H. Krein space-based H∞ fault estimation for linear discrete time-varying systems. Acta Automatica Sinica, 2008, 34(12): 1529-1533
    [17] Chadli M, Abdo A, Ding S X. H_/H∞ fault detection filter design for discrete-time Takagi-Sugeno fuzzy system. Automatica, 2013, 49(7): 1996-2005
    [18] Ding S X, Jeinsch T, Frank P M, Ding E L. A unified approach to the optimization of fault detection systems. International Journal of Adaptive Control and Signal Processing, 2000, 14(7): 725-745
    [19] Li X B. Fault Detection Filter Design for Linear Systems [Ph.D. dissertation], Louisiana State University, USA, 2009
    [20] Li X B, Zhou K M. A time domain approach to robust fault detection of linear time-varying systems. Automatica, 2009, 45(1): 94-102
    [21] Li X B, Liu H H T. Characterization of H_ index for linear time-varying systems. Automatica, 2013, 49(5): 1449-1457
    [22] Li Y Y Zhong M Y. On designing robust H∞ fault detection filter for linear discrete time-varying systems with multiple packet dropouts. Acta Automatica Sinica, 2010, 36(12): 1788-1796
    [23] Wang J L, Yang G, Liu J. An LMI approach to H_-index and mixed H_-/H∞ fault detection observer design. Automatica, 2007, 43(9): 1656-1665
    [24] Zhong M Y, Ding S X, Ding E L. Optimal fault detection for linear discrete time-varying systems. Automatica, 2010, 46(8): 1395-1400
    [25] Zhong M, Li S, Zhao Y. Robust H∞ fault detection for uncertain LDTV systems using Krein space approach. International Journal of Innovative Computing, Information and Control, 2013, 9(4): 1637-1649
    [26] Dong H L, Wang Z D, Gao H J. On design of quantized fault detection filters with randomly occurring nonlinearities and mixed time-delays. Signal Processing, 2012, 92(4): 1117-1125
    [27] Dong Q C, Zhong M Y, Ding S X. Active fault tolerant control for a class of linear time-delay systems in finite frequency domain. International Journal of Systems Science, 2012, 43(3): 543-551
    [28] Feng J, Zhao Q, Wang S Q. Closed-loop design of fault detection for networked non-linear systems with mixed delays and packet losses. IET Control Theory and Applications, 2013, 7(6): 858-868
    [29] Li X J, Yang G H. Fault detection filter design for stochastic time-delay systems with sensor faults. International Journal of Systems Science, 2012, 43(8): 1504-1518
    [30] Ye D, Yang G H. Adaptive fault-tolerant control for a class of nonlinear systems with time delay. International Journal of Systems Science, 2008, 39(1): 43-56
    [31] Zhang K, Jiang B, Cocquempot V. Fast adaptive fault estimation and accommodation for nonlinear time-varying delay systems. Asian Journal of Control, 2009, 11(6): 643-652
    [32] Zhao H, Zhong M, Zhang M. H∞ fault detection for linear discrete time-varying systems with delayed state. IET Control Theory and Applications, 2010, 4(11): 2303-2314
    [33] Shen B, Ding S X, Wang Z D. Finite-horizon H∞ fault estimation for linear discrete time-varying systems with delayed measurements. Automatica, 2013, 49(1): 293-296
    [34] He X, Wang Z D, Zhou D H. Networked fault detection with random communication delays and packet losses. International Journal of Systems Science, 2008, 39(11): 1045-1054
    [35] He X, Wang Z D, Zhou D H. Robust fault detection for networked systems with communication delay and data missing. Automatica, 2009, 45(11): 2634-2639
    [36] Wang Y, Ding S X, Ye H. A new fault detection scheme for networked control systems subject to uncertain time-varying delay. IEEE Transactions on Signal Processing, 2008, 56(10): 5258-5268
    [37] Zhang Y, Fang H J, Jiang T Y. Fault detection for nonlinear networked control systems with stochastic interval delay characterisation. International Journal of Systems Science, 2012, 43(5): 952-960
    [38] Zhou Dong-Hua, Liu Yang, He Xiao. Review on fault diagnosis techniques for closed-loop systems. Acta Automatica Sinica, 2013, 39(11): 1933-1943 (in Chinese)
    [39] Hassibi B, Sayed A H, Kailath T. Indefinite Quadratic Estimation and Control: A Unified Approach to H2 and H∞ Theories. PA: SIAM, Philadelphia, 1999. 31-50
  • 加载中
计量
  • 文章访问数:  1865
  • HTML全文浏览量:  46
  • PDF下载量:  1115
  • 被引次数: 0
出版历程
  • 收稿日期:  2013-10-23
  • 修回日期:  2013-11-23
  • 刊出日期:  2014-07-20

目录

    /

    返回文章
    返回