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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
P. Zhang and S. X. Ding, “Observer-based fault detection of linear time-varying systems (in German),” Automatisierungstechnik, vol. 52, pp. 370–376, 2004.
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.
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.
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.
X. Li, Fault Detection Filter Design for Linear Systems.Thesis of Louisiana State University, 2009.
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.
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.
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.
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.
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.
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.
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.
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.
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.
D. Henry and A. Zolghadri, “Design and analysis of robust residual generators for systems under feedback control,” Automatica, vol. 41, pp. 251–264, 2005.
J. Bokor and G. Balas, “Detection filter design for LPV systems - a geometric approach,” Automatica, vol. 40, pp. 511–518, 2004.
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.
F. M. Callier and C. A. Desoer, Linear System Theory. New York: Springer-Verlag, 1991.
S. X. Ding, Model-Based Fault Diagnosis Techniques - Design Schemes, Algorithms and Tools, 2nd Edition. London: Springer-Verlag, 2013.
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.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2021 Springer-Verlag GmbH Germany, part of Springer Nature
About this chapter
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
DOI: https://doi.org/10.1007/978-3-662-62004-5_7
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-62003-8
Online ISBN: 978-3-662-62004-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)