Skip to main content
Have a personal or library account? Click to login
Algebraic approach for model decomposition: Application to fault detection and isolation in discrete-event systems Cover

Algebraic approach for model decomposition: Application to fault detection and isolation in discrete-event systems

Open Access
|Mar 2011

References

  1. Bavishi, S. and Chong, E. (1994). Automated fault diagnosis using a discrete event systems framework,, pp. 213-218.
  2. Benveniste, A., Fabre, E., Haar, S. and Jard, C. (2003). Diagnosis of asynchronous discrete event systems: A net unfolding approach,(5): 714-727.
  3. Berdjag, D., Christophe, C. and Cocquempot, V. (2006a). An algebraic method for nonlinear system decomposition,, pp. 42-53.
  4. Berdjag, D., Christophe, C. and Cocquempot, V. (2006b). Nonlinear model decomposition for fault detection and isolation system design,, pp. 3321-3326.
  5. Berdjag, D., Christophe, C., Cocquempot, V. and Jiang, B. (2006c). Nonlinear model decomposition for robust fault detection and isolation using algebraic tools,(6): 1337-1353.
  6. Blanke, M., Kinnaert, M., Lunze, J. and Staroswiecki, M. (2003)., Springer, Berlin.
  7. Boel, R. and Jiroveanu, G. (2004). Distributed contextual diagnosis for very large systems,, pp. 343-348.
  8. Boubour, R., Jard, C., Aghasaryan, A., Fabre, E. and Benveniste, A. (1997). A Petri net approach to fault detection and diagnosis in distributed systems (Parts 1 and 2),, pp. 720-731.
  9. Chow, E. and Willsky, A. (1984). Analytical redundancy and the design of robust failure detection systems,(7): 603-614.
  10. Cox, D., Little, J. and O'Shea, D. (1991)., Springer-Verlag, New York, NY.
  11. Diop, S. (1991). Elimination in control theory,: 17-32.
  12. Fliess, M. and Join, C. (2003). An algebraic approach to fault diagnosis for linear systems,, pp. 1-9.
  13. Fliess, M., Join, C. and Sira-Ramírez, H. (2004). Robust residual generation for linear fault diagnosis: An algebraic setting with examples,(20): 1223-1242.
  14. Gertler, J. (1991). Analytical redundancy methods in fault detection and isolation—Survey and synthesis,, Vol. 1, pp. 9-21.
  15. Gertler, J. J. (1998)., Marcel Dekker, New York, NY.
  16. Giua, A. (1997). Petri net state estimators based on event observation,, pp. 4086-4091.
  17. Hadjicostis, C. and Verghese, G. (1999). Monitoring discrete event systems using Petri net embeddings,S. Donatelli and J. Kleijn (Eds.),, Lecture Notes in Computer Science, Vol. 1639, Springer Verlag, Berlin/Heidelberg, pp. 188-207, DOI: 10.1007/3-540-48745-X_12.
  18. Hammouri, H., Kinnaert, M. and El Yaagoubi, E. (2001). A geometric approach to fault detection and isolation for bilinear systems,(9): 1451-1455.
  19. Hamscher, W., Console, L. and Kleer, J. D. (1992)., Morgan Kaufmann Publishers, San Mateo, CA.
  20. Hartmanis, J. and Stearns, R. (1966)., Prentice-Hall, New York, NY.
  21. Hillston, J. (1996)., Cambridge University Press, Cambridge.
  22. Isermann, R. (1984). Process fault-detection based on modelling and estimation methods—A survey,(4): 387-404.
  23. Isermann, R. (2005). Model-based filt detection and analysis—Status and application,(1): 71-85.
  24. Isermann, R. and Freyermuth, B. (1991). Process fault diagnosis based on process model knowledge, Part 1: Principles for fault diagnosis with parameter estimation,(4): 620-626.
  25. Isidori, A. (1995)., 3rd Edn., Springer-Verlag, Berlin.
  26. Jiang, B., Staroswiecki, M. and Cocquempot, V. (2004). Fault diagnosis based on adaptive observer for a class of nonlinear systems with unknown parameters,(4): 415-426.
  27. Jiang, B., Staroswiecki, M. and Cocquempot, V. (2006). Fault accommodation for nonlinear dynamic systems,(9): 1578-1583.
  28. Kinnaert, M. (1999). Robust fault detection based on observers for bilinear systems,(11): 1829-1842.
  29. Lafortune, S., Teneketzis, D., Sengupta, R., Sampath, M. and Sinnamohideen, K. (2001). Failure diagnosis of dynamic systems: An approach based on discrete event systems,, pp. 2058-2071.
  30. Lefebvre, D. (1999). Failure detection and isolation for manufacturing systems,: V.33-V.44.
  31. Leuschen, M., Walker, I. and Cavallaro, J. (2005). Fault residual generation via nonlinear analytical redundancy,(3): 452-458.
  32. Lin, F. (1994). Diagnosability of discrete event systems and its applications,(2): 197-212, DOI: 10.1007/BF01441211.
  33. Lootsma, T. (2001)., Ph.D. thesis, Aalborg University, Aalborg.
  34. Maquin, D., Cocquempot, V., Cassar, J., Staroswiecki, M. and Ragot, J. (1997). Generation of analytical redundancy relations for FDI purposes,, pp. 270-276.
  35. Maquin, D., Luong, M. and Ragot, J. (1997). Fault detection and isolation and sensor network design,(2): 393-406.
  36. Patton, R. (1994). Robust model-based fault diagnosis: The state of the art,, Vol. 1, pp. 1-24.
  37. Sampath, M., Sengupta, R., Lafortune, S., Sinnamohideen, K. and Teneketzis, D. (1995). Diagnosability of discreteevent systems,(9): 1555-1575.
  38. Sampath, M., Sengupta, R., Lafortune, S., Sinnamohideen, K. and Teneketzis, D. (1996). Failure diagnosis using discrete-event models,(2): 105-124.
  39. Shumsky, A. (1991). Fault isolation in nonlinear dynamic systems by functional diagnosis,: 148-155.
  40. Shumsky, A. (2007). Redundancy relations for fault diagnosis in nonlinear uncertain systems,(4): 477-489, DOI: 10.2478/v10006-007-0040-1.
  41. Shumsky, A. and Zhirabok, A. (2006). Nonlinear diagnostic filter design: Algebraic and geometric points of view,(1): 115-127.
  42. Staroswiecki, M. and Comtet-Varga, G. (2001). Analytical redundancy relations for fault detection and isolation in algebraic dynamic systems,(5): 687-699.
  43. Vereshchagin, N. and Shen, A. (2002)., Student Mathematical Library, Vol 17, American Mathematical Society, Providence, RI.
  44. Zad, H., Kwong, R. and Wonham, W. (2003). Fault diagnosis in discrete-event systems: Framework and model reduction,(7): 1199-1212.
  45. Zad, S. H. (1999)., Ph.D. thesis, University of Toronto, Toronto.
  46. Zhirabok, A. (2006). Nonlinear dynamic systems: Their canonical decomposition based on invariant functions,(4): 517-528.
  47. Zhirabok, A. and Shumsky, A. (1993). A new mathematical techniques for nonlinear systems research,, pp. 485-488.
DOI: https://doi.org/10.2478/v10006-011-0008-z | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
Language: English
Page range: 109 - 125
Published on: Mar 28, 2011
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2011 Denis Berdjag, Vincent Cocquempot, Cyrille Christophe, Alexey Shumsky, Alexey Zhirabok, published by University of Zielona Góra
This work is licensed under the Creative Commons License.