Fault detection in nonlinear systems via linear methods

• Autorzy: Zhirabok A. , Shumsky A. , Solyanik S. , Suvorov A.

Identyfikatory

DOI

10.1515/amcs-2017-0019

• Języki publikacji: EN

Abstrakty

EN

The problem of robust linear and nonlinear diagnostic observer design is considered. A method is suggested to construct the observers that are disturbance decoupled or have minimal sensitivity to the disturbances. The method is based on a logic-dynamic approach which allows us to consider systems with non-differentiable nonlinearities in the state equations by methods of linear algebra.

Słowa kluczowe

EN

nonlinear dynamic system; diagnostic observer; robustness; nondifferentiable nonlinearity; logic dynamic approach

PL

układ dynamiczny; układ nieliniowy; obserwator diagnostyczny; odporność na uszkodzenia

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2017
• Tom: Vol. 27, no. 2
• Strony: 261--272
• Opis fizyczny: Bibliogr. 23 poz., tab., wykr.

Twórcy

autor

Zhirabok A.

• Department of Automation and Control, Far Eastern Federal University, Sukhanova, 8, Vladivostok, 690990, Russia; Department of Robotic Systems, Institute of Marine Technology Problems, Sukhanova, 5, Vladivostok, 690990, Russia

autor

Shumsky A.

• Department of Automation and Control, Far Eastern Federal University, Sukhanova, 8, Vladivostok, 690990, Russia; Department of Automatic Control, Institute of Applied Mathematics, Radio, 5, Vladivostok, 690014, Russia

autor

Solyanik S.

• Department of Automation and Control, Far Eastern Federal University, Sukhanova, 8, Vladivostok, 690990, Russia

autor

Suvorov A.

• Department of Automation and Control, Far Eastern Federal University, Sukhanova, 8, Vladivostok, 690990, Russia

Bibliografia

• [1] Alcorta-Garcia, E. and Frank, P. (1997). Deterministic nonlinear observerbased approach to fault diagnosis: A survey, Control Engineering Practice 5(5): 663–670.
• [2] Boulkroune, B., Djemili, I., Aitouche, A., and Cocquempot, V. (2013). Robust nonlinear observer design for actuator fault detection in diesel engines, International Journal of Applied Mathematics and Computer Science 23(3): 557–569, DOI: 10.2478/amcs-2013-0042.
• [3] Blanke, M., Kinnaert, M., Lunze, J., and Staroswiecki, M. (2006). Diagnosis and Fault-Tolerant Control, Springer, Berlin.
• [4] Caccavale, F. and Villiani, L. (Eds.) (2002). Fault Diagnosis and Tolerance for Mechatronic Systems: Recent Advances, Springer, Berlin.
• [5] Ding, S. (2013). Model-Based Fault Diagnosis Techniques—Design Schemes, Algorithms and Tools, 2nd Edn., Springer, London.
• [6] Ducard, G.J.J. (2015). SMAC-FDI: A single model active fault detection and isolation system for unmanned aircraft, International Journal of Applied Mathematics and Computer Science 25(1): 189–201, DOI: 10.1515/amcs-2015-0014.
• [7] Filaretov V., Vukobratovic M., and Zhirabok A. (2003). Parity relation approach to fault diagnosis in manipulation robots, Mechatronics 13(2): 141–152.
• [8] Filaretov, V. and Zhirabok, A. (2006). Logic-dynamic approach to fault diagnosis in mechatronic systems, International Journal of Advanced Robotic Systems 3(4): 285–294.
• [9] Frank, P. (1990). Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy—A survey and some new results, Automatica 26(3): 459–474.
• [10] Gertler, J. (1993). Residual generation in model-based fault diagnosis, Theory and Advanced Technology 9(1): 259–285.
• [11] Low, X. and Willsky, A. and Verghese, G. (1996). Optimally robust redundancy relations for failure detection in uncertain systems, Automatica 22(3): 333–344.
• [12] Patton, R. (1994). Robust model-based fault diagnosis: The state of the art, IFAC Symposium SAFEPROCESS’2004, Espoo, Finland, pp. 1–24.
• [13] Patton, R., Frank, P. and Clark, R. (2000). Issues of Fault Diagnosis for Dynamic Systems, Springer, London.
• [14] Persis, D.C. and Isidori, A. (2001). A geometric approach to nonlinear fault detection and isolation, IEEE Transactions on Automatic Control AC–46(6): 853–865.
• [15] Russell, E., Chiang, L., and Chiang, L. (2001). Fault Detection and Diagnosis in Industrial Systems, Springer, Berlin.
• [16] Samy, I., Postlethwaite, I. and Gu, D. (2011). Survey and application of sensor fault detection and isolation schemes, Control Engineering Practice 19(5): 658–674.
• [17] Schreier, G., Ragot, J., Patton, R., and Frank, F. (1997). Observer design for a class of nonlinear systems, IFAC Symposium SAFEPROCESS’1997, Hull, UK, pp. 498–503.
• [18] Simani, S., Fantuzzi, C., and Patton, R. (2002). Model-Based Fault Diagnosis in Dynamic Systems Using Identification, Springer, Berlin.
• [19] Shumsky, A. and Zhirabok, A. (2006). Nonlinear diagnostic filter design: Algebraic and geometric points of view, International Journal of Applied Mathematics and Computer Science 16(1): 115–127.
• [20] Zhirabok, A. and Usoltsev, S. (2002). Fault diagnosis for nonlinear dynamic systems via linear methods, 15th World Congress IFAC, Barcelona, Spain, (on CD ROM).
• [21] Zhirabok, A., Kucher, D., and Filaretov, V. (2010). Achieving robustness at diagnosis of nonlinear systems, Automation and Remote Control 71(1): 142–155.
• [22] Zhirabok, A. and Shumsky, A. (2010). Linear methods in observability and controllability of nonlinear systems, 8th IFAC Symposium on Nonlinear Systems, Bologna, Italy, pp. 308–313.
• [23] Zhirabok, A. and Shumsky, A. (2013). Logic-dynamic approach to the robust fault diagnosis in nonlinear systems, 2013 Conference on Control and Fault Tolerant Systems, Nice, France, pp. 190–195.

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).