Skip to main content
Log in

Strong Tracking Filter-Based Fault Diagnosis of Networked Control System with Multiple Packet Dropouts and Parameter Perturbations

  • Published:
Circuits, Systems, and Signal Processing Aims and scope Submit manuscript

Abstract

This paper mainly discusses the fault diagnosis problem for a class of nonlinear dynamic discrete systems with parameter perturbations and network-induced packet dropouts based on a recursive strong tracking filter. Due to the limited network bandwidth, the data transmitted via the Internet from different sensors may suffer from independent packet dropouts. And then, a series of Bernoulli sequences is employed to simulate the multiple data loss rates. In the residual design process, for a strong tacking filter (STF) which appears as an enhanced extended Kalman filter by introducing a fading factor in the filter structure, both parameter perturbations and packet dropouts are considered. In addition, a small change is made in the fading factor calculating equation in order to ensure the tracking performance of STF. Taking advantage of its good robustness against sudden changes, a novel system consisting of two STF-based models is constructed and the bias between their estimated states is treated as a residual. A fault can be alarmed through the Monte Carlo simulation method opted threshold. Meanwhile, it can also be isolated by the idea of residual contributing degree. Some simulation studies are carried out on an Internet-based three-tank system to show the effectiveness of the proposed approach.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. M.Z. Chen, D.H. Zhou, An adaptive fault prediction method based on strong tracking filter. J. Shanghai Marit. Univ. 22(3), 35–45 (2001)

    Google Scholar 

  2. W.G. Ding, Z.H. Mao, B. Jiang, W. Chen, Fault detection for a class of nonlinear networked control systems with Markov transfer delays and stochastic packet drops. Circuits Syst. Signal Process. 34(4), 1211–1231 (2015)

    Article  MathSciNet  Google Scholar 

  3. H.J. Fang, H. Ye, M.Y. Zhong, Fault diagnosis of networked control systems. Annu. Rev. Control. 31(1), 55–68 (2007)

    Article  Google Scholar 

  4. J. Feng, S.Q. Wang, Q. Zhao, Closed-loop design of fault detection for networked non-linear systems with mixed delays and packet losses. IET Control Theory Appl. 7(6), 858–868 (2013)

    Article  MathSciNet  Google Scholar 

  5. H.J. Gao, T.W. Chen, J. Lam, A new delay system approach to network-based control. Automatica 44(1), 39–52 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  6. X. He, Z.D. Wang, X.F. Wang, D.H. Zhou, Networked strong tracking filtering with multiple packet dropouts: algorithms and applications. IEEE Trans. Ind. Electron. 61(3), 1454–1463 (2014)

    Article  Google Scholar 

  7. D. Huang, S.K. Nguang, Robust fault estimator design for uncertain networked control systems with random time delays: An ILMI approach. Inf. Sci. 180(3), 465–480 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  8. Z.H. Huo, Y. Zheng, C. Xu, A robust fault-tolerant control strategy for networked control systems. J. Netw. Comput. Appl. 34(2), 708–714 (2011)

    Article  Google Scholar 

  9. S. Jiang, H.J. Fang, F. Pan, Robust fault detection for nonlinear networked systems with multiple fading measurements. Circuit Syst. Signal Process. (2015). doi:10.1007/s00034-015-0003-y

  10. J. Ma, S.L. Sun, Optimal linear estimators for system with random sensor delays, multiple packet dropouts and uncertain observations. IEEE Trans. Signal Process. 59(11), 5181–5192 (2011)

    Article  MathSciNet  Google Scholar 

  11. Z.H. Mao, B. Jiang, P. Shi, Observer-based fault-tolerant control for a class of networked control systems with transfer delays. J. Frankl. Inst. 348(4), 763–776 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  12. X.B. Wan, H.J. Fang, S. Fu, Observer-based fault detection for networked discrete-time infinite-distributed delay systems with packet dropouts. Appl. Math. Model. 36(1), 270–278 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  13. J.F. Wang, C.F. Liu, H.Z. Yang, Stability of a class of networked control systems with Markovian characterization. Appl. Math. Model. 36(7), 3168–3175 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  14. Y.Q. Wang, H. Ye, S. Ding, G.Z. Wang, Fault detection of networked control systems based on optimal robust fault detection filter. Acta Autom. Sin. 34(12), 1534–1539 (2008)

    Article  MathSciNet  Google Scholar 

  15. Y.Q. Wang, H. Ye, S. Ding, G.Z. Wang, Fault detection of networked control systems subject to access constraints and random packet dropout. Acta Autom. Sin. 35(9), 1230–1234 (2009)

    Google Scholar 

  16. Y.Q. Wang, S.Y. Zhang, Z. Li, M.S. Zhang, Fault detection for a class of nonlinear singular systems over networks with mode-dependent time delays. Circuit Syst. Signal Process. 33(10), 3085–3106 (2014)

    Article  MathSciNet  Google Scholar 

  17. C.L. Wen, Z.G. Chen, D.H. Zhou, Joint state and parameter estimation for multisensor nonlinear dynamic systems on the basis of strong tracking filter. Acta Electron. Sin. 30(11), 1715–1717 (2002)

    Google Scholar 

  18. S.H. Yang, X. Chen, J.L. Alty, Design issues and implementation of internet-based process control systems. Control Eng. Pract. 11(6), 709–720 (2003)

    Article  Google Scholar 

  19. K.Y. You, L.H. Xie, Survey of recent progress in networked control systems. Acta Autom. Sin. 39(2), 101–117 (2013)

    Article  MathSciNet  Google Scholar 

  20. D. Yue, Q.L. Han, J. Lam, Network-based robust \(H_{\infty }\) control of systems with uncertainty. Automatica 41(6), 999–1007 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  21. H. Zhang, X.Y. Huang, J.M. Wang, H.R. Karimi, Robust energy-to-peak sideslip angle estimation with applications to ground vehicles. Mechatronics. (2014). http://dx.doi.org/10.1016/j.mechatronics.2014.08.003

  22. H. Zhang, J.M. Wang, State estimation of discrete-time Takagi-Sugeno fuzzy systems in a network environment. IEEE Trans. Cybern. 1–12 (2014)

  23. H. Zhang, J.M. Wang, NOx sensor ammonia-cross-sensitivity factor estimation in diesel engine selective catalytic reduction systems. J. Dyn. Syst-T. ASME. 137(6), 061015-1–061015-9 (2015)

    Google Scholar 

  24. H. Zhang, J.M. Wang, Robust two-mode-dependent controller design for networked control systems with random delays modeled by Markov chains. Int. J. Control. (2015). doi:10.1080/00207179.2015.1048293

  25. Y. Zhang, H.J. Fang, Z.X. Liu, Fault detection for nonlinear networked control systems with Markov data transmission pattern. Circuit Syst. Signal Process. 31(4), 1343–1358 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  26. Y. Zhang, H.J. Fang, Z. Luo, \(H_{\infty } \)-based fault detection for nonlinear networked systems with random packet dropout and probabilistic interval delay. J. Syst. Eng. Electron. 22(5), 825–831 (2011)

    Article  MathSciNet  Google Scholar 

  27. Y. Zhang, Z.X. Liu, H.J. Fang, H.B. Chen, \(H_{\infty }\) fault detection for nonlinear networked systems with multiple channels data transmission pattern. Inf. Sci. 221, 534–543 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  28. Y. Zhang, Z.X. Liu, B. Wang, Robust fault detection for nonlinear networked systems with stochastic interval delay characteristics. ISA Trans. 50(4), 521–528 (2011)

    Article  Google Scholar 

  29. M.Y. Zhao, H.P. Liu, Z.J. Li, D.H. Sun, K.P. Liu, Fault tolerant control for networked control systems with access constraints. Acta Autom. Sin. 38(7), 1119–1126 (2012)

    Article  MathSciNet  Google Scholar 

  30. D.H. Zhou, P.M. Frank, Strong tracking filtering of nonlinear time-varying stochastic systems with colored noise: Application to parameter estimation and empirical robustness analysis. Int. J. Control 65(2), 295–307 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  31. D.H. Zhou, X. He, Z.D. Wang, G.P. Liu, Leakage fault diagnosis for an internet-based three-tank system: an simulation study. IEEE Trans. Control Syst. Technol. 20(4), 857–870 (2012)

    Article  Google Scholar 

  32. Z.Q. Zhu, X.C. Jiao, Fault detection based on \(H_{\infty }\) states observer for networked control systems. J. Syst. Eng. Electron. 20(2), 379–387 (2009)

    MATH  Google Scholar 

Download references

Acknowledgments

This work is supported by National Natural Science Foundation of China (Grant No. 61473127). The authors would like to thank the editor and the reviewers for their helpful suggestions to improve the quality of this correspondence.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Huajing Fang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Qin, X., Fang, H. & Liu, X. Strong Tracking Filter-Based Fault Diagnosis of Networked Control System with Multiple Packet Dropouts and Parameter Perturbations. Circuits Syst Signal Process 35, 2331–2350 (2016). https://doi.org/10.1007/s00034-015-0142-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00034-015-0142-1

Keywords

Navigation