Skip to main content

Fault Detection in Linear Time-Varying Systems

  • Chapter
  • First Online:
Advanced methods for fault diagnosis and fault-tolerant control
  • 1156 Accesses

Abstract

Our study on fault detection in linear discrete time-varying (LDTV) systems is highly motivated by the recent development in the fault detection research and application domains. Firstly, we see the demands for investigation on LDTV fault detection systems. It is evident that even for an LTI process the fault detection system with a finite residual evaluation horizon is time-varying.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. P. Zhang and S. X. Ding, “Observer-based fault detection of linear time-varying systems (in German),” Automatisierungstechnik, vol. 52, pp. 370–376, 2004.

    Article  Google Scholar 

  2. X. Li and K. Zhou, “A time domain approach to robust fault detection of linear time-varying systems,” Automatica, vol. 45, pp. 94–102, 2009.

    Article  MathSciNet  Google Scholar 

  3. P. Zhang, S. Ding, G. Wang, and D. Zhou, “Fault detection of linear discrete-time periodic systems,” IEEE Trans. on Automatic Control, vol. 50(2), pp. 239–244, 2005.

    Article  MathSciNet  Google Scholar 

  4. P. Zhang and S. X. Ding, “On fault detection in linear discrete-time, periodic, and sampled-data systems (survey),” Journal of Control Science and Engineering, pp. 1–18, 2008.

    Google Scholar 

  5. X. Li, Fault Detection Filter Design for Linear Systems.Thesis of Louisiana State University, 2009.

    Google Scholar 

  6. M. Zhong, S. X. Ding, Q. Han, and Q. Ding, “Parity space-based fault estimation for linear discrete time-varying systems,” IEEE Trans. on Autom. Contr., vol. 55, pp. 1726–1731, 2010.

    Article  MathSciNet  Google Scholar 

  7. M. Zhong, Y. Song, and S. X. Ding, “Parity space-based fault detection for linear discrete time-varying systems with unknown input,” Automatica, vol. 59, pp. 120–126, 2015.

    Article  MathSciNet  Google Scholar 

  8. T. Xue, M. Zhong, S. X. Ding, and H. Ye, “Stationary wavelet transform aided design of parity space vectors for fault detection in LDTV systems,” IET Control Theory and Applications, vol. 12, pp. 857–864, 2018.

    MathSciNet  Google Scholar 

  9. M. Zhong, D. Zhou, and S. X. Ding, “On designing \(H_{inf}\) fault detection filter for linear discrete time-varying systems,” IEEE Trans. on Autom. Control, vol. 55, pp. 1689–1695, 2010.

    Article  Google Scholar 

  10. M. Zhong, S. X. Ding, and D. Zhou, “A new scheme of fault detection for linear discrete time-varying systems,” IEEE Trans. on Automat. Contr., vol. 61, pp. 2597–2602, 2016.

    Article  MathSciNet  Google Scholar 

  11. M. Zhong, S. X. Ding, and E. L. Ding, “Optimal fault detection for linear discrete time-varying systems,” Automatica, vol. 46, pp. 1395–1400, 2010.

    Article  MathSciNet  Google Scholar 

  12. M. Zhong, T. Xue, and S. X. Ding, “A survey on model-based fault diagnosis for linear discrete time varying systems,” Neurocomputing, vol. 306, pp. 51–60, 2018.

    Google Scholar 

  13. A. Edelmayer and J. Bokor, “Optimal h-infinity scaling for sensitivity optimization of detection filters,” Int. J. of Robust and Nonlinear Contr., vol. 12, pp. 749 – 760, 2002.

    Google Scholar 

  14. A. Casavola, D. Famularo, and G. Fraze, “A robust deconvolution scheme for fault detection and isolation of uncertain linear systems: An LMI approach,” Automatica, vol. 41, pp. 1463–1472, 2005.

    Article  MathSciNet  Google Scholar 

  15. D. Henry and A. Zolghadri, “Design and analysis of robust residual generators for systems under feedback control,” Automatica, vol. 41, pp. 251–264, 2005.

    Article  MathSciNet  Google Scholar 

  16. J. Bokor and G. Balas, “Detection filter design for LPV systems - a geometric approach,” Automatica, vol. 40, pp. 511–518, 2004.

    Article  MathSciNet  Google Scholar 

  17. H. Wang and G.-H. Yang, “Integrated fault detection and control for LPV systems,” Int. J. of Robust and Nonlinear Control, vol. 19, pp. 341–363, 2009.

    Google Scholar 

  18. F. M. Callier and C. A. Desoer, Linear System Theory. New York: Springer-Verlag, 1991.

    Book  Google Scholar 

  19. S. X. Ding, Model-Based Fault Diagnosis Techniques - Design Schemes, Algorithms and Tools, 2nd Edition. London: Springer-Verlag, 2013.

    Book  Google Scholar 

  20. M. Zhong, L. Zhang, S. X. Ding, and D. Zhou, “A probabilistic approach to robust fault detection for a class of nonlinear systems,” IEEE Trans. on Indus. Elec., vol. 64, pp. 3930–3939, 2017.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Steven X. Ding .

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer-Verlag GmbH Germany, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Ding, S.X. (2021). Fault Detection in Linear Time-Varying Systems. In: Advanced methods for fault diagnosis and fault-tolerant control. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-62004-5_7

Download citation

Publish with us

Policies and ethics