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Sliding mode observers for detection and reconstruction of sensor faults. (English) Zbl 1011.93505
Summary: This paper proposes two methods for detecting and reconstructing sensor faults using sliding mode observers. In both methods, fictitious systems are introduced in which the original sensor fault appears as an actuator fault. The original sensor faults are then reconstructed using a `secondary’ sliding mode observer. For both methods, there are certain conditions which must be satisfied for successful fault detection and reconstruction. The methods are demonstrated using a chemical process example.

90B25Reliability, availability, maintenance, inspection, etc. (optimization)
93B12Variable structure systems
Full Text: DOI
[1] Chen, J.; Patton, R. J.: Robust model-based fault diagnosis for dynamic systems. (1999) · Zbl 0920.93001
[2] Chilali, M.; Gahinet, P.: H$\infty $design with pole placement constraintsan LMI approach. IEEE transactions on automatic control 41, 358-367 (1996) · Zbl 0857.93048
[3] Edwards, C.; Spurgeon, S. K.: On the development of discontinuous observers. International journal of control 59, 1211-1229 (1994) · Zbl 0810.93009
[4] Edwards, C.; Spurgeon, S. K.: A sliding mode observer based FDI scheme for the ship benchmark. European journal of control 6, 341-356 (2000) · Zbl 1293.93154
[5] Edwards, C.; Spurgeon, S. K.; Patton, R. J.: Sliding mode observers for fault detection and isolation. Automatica 36, 541-553 (2000) · Zbl 0968.93502
[6] Frank, P. M.: Analytical and qualitative model-based fault diagnosis--a survey and some new results. European journal of control 2, 6-28 (1996) · Zbl 0857.93015
[7] Hermann, G., Spurgeon, S. K., & Edwards, C. (2000). Model-based control of the HDA-plant, a non-linear, large scale chemical process, using sliding mode and H\infty approaches. UKACC Control Conference, Cambridge, 2000.
[8] Hermans, F. J. J., & Zarrop, M. B. (1996). Sliding mode observers for robust sensor monitoring. 13th IFAC world congress, San Francisco (pp. 211-216).
[9] Magni, J. F.; Mouyon, P.: On residual generation by observer and parity space approaches. IEEE transactions on automatic control 39, 441-447 (1994) · Zbl 0800.93183
[10] Patton, R. J.; Frank, P. M.; Clark, R. N.: Fault diagnosis in dynamic systems: theory and application. (1989)
[11] Sreedhar, R., Fernandez, B., & Masada, G. Y. (1993). Robust fault detection in nonlinear systems using sliding mode observers. IEEE conference on control applications, Vancouver (pp. 715-721).
[12] Tan, C. P., & Edwards, C. (2000). An LMI approach for designing sliding mode observers. IEEE conference on decision and control, Sydney (pp. 2587-2592).
[13] Utkin, V. I.: Sliding modes in control optimization. (1992) · Zbl 0748.93044
[14] Zhang, Q.; Basseville, M.; Benveniste, A.: Fault detection and isolation in nonlinear dynamic systemsa combined input-output and local approach. Automatica 34, 1359-1373 (1998) · Zbl 0961.93007