Abstract
Fault estimation is a main issue in the fault diagnosis framework. As illustrated in previous chapters, fault estimation can be embedded in an optimal fault detection solution, and further delivers detailed information about the fault, after this fault is detected. In this chapter, we study the fault estimation problem defined in the following context.
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References
H. Niemann, A. Saberi, A. Stoovogel, and P. Sannuti, “Optimal fault estimation,” Proc. of the 4th IFAC Symp. SAFEPROCESS, vol. 1, pp. 262–267, 2000.
H. Niemann and J. J. Stoustrup, “Design of fault detectors using h-infinity optimization,” Proc. of the 39th IEEE CDC, 2000.
A. Saberi, A. Stoovogel, P. Sannuti, and H. Niemann, “Fundamental problems in fault detection and identification,” Int. J. Robust Nonlinear Contr., vol. 10, pp. 1209–1236, 2000.
H. Wang and G.-H. Yang, “Fault estimations for uncertain linear discrete-time systems in low frequency domain,” Proc. of the 2007 ACC, pp. 1124–1129, 2007.
H. Wang and G.-H. Yang, “Fault estimations for linear systems with polytopic uncertainties,” Int. J. Systems, Control and Communications, vol. 1, pp. 53–71, 2008.
G. Murad, I. Postlethwaite, and D.-W. Gu, “A robust design approach to integrated control and diagnostics,” Proc. of the 13th IFAC Word Congress, vol. 7, pp. 199–204, 1996.
C. N. Nett, C. Jacobson, and A. T. Miller, “An integrated approach to controls and diagnostics,” Proc. of ACC, pp. 824–835, 1988.
M. L. Tyler and M. Morari, “Optimal and robust design of integrated control and diagnostic modules,” Proc. of ACC, pp. 2060–2064, 1994.
S. X. Ding, Model-Based Fault Diagnosis Techniques - Design Schemes, Algorithms, and Tools. Springer-Verlag, 2008.
K. Busawon and P. Kabore, “Disturbance attenuation using proportional integral observers,” Int. J. Contr., vol. 74, pp. 618–627, 2001.
M. Saif, “Reduced-order proportional integral observer with application,” J. Guidance control dynamics, vol. 16, pp. 985–988, 1993.
B. Shafai, C. T. Pi, and S. Nork, “Simultaneous disturbance attenuation and fault detection using proportional integral observers,” Proc. ACC, pp. 1647–1649, 2002.
Z. Gao and D. Ho, “Proportional multiple-integral observer design for descriptor systems with measurement output disturbances,” IEE Proc. - Control Theory Appl., vol. 151(3), pp. 279–288, 2004.
Z. Gao and D. W. C. Ho, “State/Noise estimator for descriptor systems with application to sensor fault diagnosis,” IEEE Trans. Signal Processing, vol. 54, pp. 1316–1326, 2006.
Q. P. Ha and H. Trinh, “State and input simultaneous estimation for a class of nonlinear systems,” Automatica, vol. 40, pp. 1779–1785, 2004.
Z. Gao and S. X. Ding, “Actuator fault robust estimation and fault-tolerant control for a class of nonlinear descriptor systems,” Automatica, vol. 43, pp. 912–920, 2007.
Z. Gao, X. Shi, and S. Ding, “Fuzzy state/disturbance observer design for T-S fuzzy systems with application to sensor fault estimation,” IEEE Trans. on Syst. Man and Cyber - Part B, Cybernetics, vol. 38, pp. 875–880, 2008.
H. W. Sorenson, “Least-squares estimation: From Gauss to Kalman,” IEEE Spectrum, pp. 63–68, 1970.
P. Swerling, “Modern state estimation methods from the viewpoint of the method of least squares,” IEEE Trans. on Autom. Contr., vol. 16, pp. 707–719, 1971.
J. Willems, “Deterministic least squares filtering,” Journal of Econometrics, vol. 118, pp. 341–373, 2004.
T. Kailath, A. Sayed, and B. Hassibi, Linear Estimation. New Jersey: Prentice Hall, 1999.
J. Gertler, “Survey of model-based failure detection and isolation in complex plants,” IEEE Control Systems Magazine, vol. 3, pp. 3–11, 1988.
R. Isermann, “Process fault detection based on modeling and estimation methods - a survey,” Automatica, vol. 20, pp. 387–404, 1984.
R. Isermann, “Supervision, fault-detection and fault-diagnosis methods -an introduction,” Control Engineering Practice, vol. 5 (5), pp. 639–652, 1997.
R. Isermann, Fault Diagnosis Systems. Berlin Heidelberg: Springer-Verlag, 2006.
S. Simani, S. Fantuzzi, and R. J. Patton, Model-Based Fault Diagnosis in Dynamic Systems Using Identification Techniques. London: Springer-Verlag, 2003.
C. Tan and C. Edwards, “Sliding mode observers for detection and reconstruction of sensor faults,” Automatica, vol. 38, pp. 1815–1821, 2002.
W. Chen and M. Saif, “A sliding mode observer-based strategy for fault detection, isolation, and estimation in a class of lipschitz nonlinear systems,” Int. J. of Syst. Science, vol. 38, pp. 943–955, 2007.
H. Alwi, C. Edwards, and C. P. Tan, Fault Detection and Fault-Tolerant Control Using Sliding Modes. Springer-Verlag, 2011.
D. H. Zhou and P. M. Frank, “Strong tracking filtering of nonlinear time-varying stochastic systems with coloured noise: Application to parameter estimation and empirical robustness analysis,” Int. J. Control, vol. 65, pp. 295–307, 1996.
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Ding, S.X. (2021). Fault Estimation in Linear Dynamic Systems. In: Advanced methods for fault diagnosis and fault-tolerant control. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-62004-5_8
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DOI: https://doi.org/10.1007/978-3-662-62004-5_8
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