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2007 | 17 | 4 | 477-489
Tytuł artykułu

Redundancy relations for fault diagnosis in nonlinear uncertain systems

Autorzy
Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The problem of fault detection and isolation in nonlinear uncertain systems is studied within the scope of the analytical redundancy concept. The problem solution involves checking the redundancy relations existing among measured system inputs and outputs. A novel method is proposed for constructing redundancy relations based on system models described by differential equations whose right-hand sides are polynomials. The method involves a nonlinear transformation of the initial system model into a strict feedback form. Algebraic and geometric tools are used for this transformation. The features of the method are made particular for uncertain systems with a linear structure.
Rocznik
Tom
17
Numer
4
Strony
477-489
Opis fizyczny
Daty
wydano
2007
(nieznana)
2006-12-15
otrzymano
2007-03-05
poprawiono
2007-07-07
Twórcy
  • Institute for Marine Technology Problems, Far Eastern Branch of the Russian Academy of Sciences, Sukhanova 5a, Vladivostok, 690950, Russia
Bibliografia
  • Chow E. Y. and A.S. Willsky. (1984): Analytical redundancy and the design of robust failure detection systems. IEEE Transactions on Automatic Control, Vol.AC-29,No.7, pp.603-614.
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  • Cox D., Ltle J. and D. O'Shea. (1992): Ideals, Varieties and Algorithms. New York: Springer.
  • De Persis C. and A. Isidori. (2001): A geometric approach to nonlinear fault detection and isolation. IEEE Transactions on Automatic Control, Vol.AC-46, No.6, pp.853-865.
  • De Persis C. and A. Isidori. (2002): Fault detection filters. International Journal of Robust and Nonlinear Control, Vol.12, No.6, pp.729-747.
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  • Diop S. (1991): Elimination in control theory. - Mathematics of Control, Signals, and Systems, Vol.14, No.1, pp.459-474
  • Frank P.M. (1990): Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy- A survey and some new results. Automatica, Vol.26, No3, pp.459-474.
  • Gertler J. and M.M. Kunwer. (1993): Optimal residual decoupling for robust fault diagnosis. Proceedings of the International Conference Tooldiag'93, Toulouse, France, pp.436-452.
  • Isermann R. (1984): Process fault detection based on modeling and estimationmethods: A survey. Automatica, Vol.20, No.4, pp.387-404.
  • Isidori A. (1989): Nonlinear Control Systems. Berlin: Springer.
  • Lou X.C., Willsky A.S. and G.L. Verghese.(1986): Optimally robust redundancy relations for failure detection in uncertain systems. Automatica, Vol.22, No.3,pp.333-344.
  • Massoumnia M. A. (1986): A geometric approach to the synthesis of failure detection filters. IEEE Transactions on Automatic Control, Vol.AC-31, No.9, pp.839-846.
  • Massoumnia M. A., G. C. Verghese and A.S. Willsky. (1989): Failure detection and identification. IEEE Transactions on Automatic Control, Vol.AC-34,No.3, pp.316-323.
  • Medvedev A. (1994): Pary space method: A continuous time approach. Proceedings of the American Control Conference, Baltimore, Vol.1, pp.662-665.
  • Mironovskii L.A. (1980): Functional diagnosis of dynamic systems. Automation and Remote Control, Vol.41, No.8, pp.1122-1143.
  • Park J., G. Rizzoni and W.B. Ribbens. (1994): On the representation of sensor faults in fault detection filters. Automatica, Vol.30, No.11, pp.1793-1795.
  • Patton R. and S. Kangethe. (1989): Robust fault diagnosis using eigen structure assignment of observers. In: Fault Diagnosis in Dynamic Systems. Theory and Application (Patton R.J., Frank P.M., Clark R.N. N.Y., Eds.), Englewood Cliffs: Prentice Hall,pp.99-154.
  • Pekpe, K. M., G. Mourot and J. Ragot. (2004): Subspace method for sensors fault detection and isolation -application to grinding circuit monitoring. Proceedings of the 11th IFAC Symposium on Automation in Mining, Mineral and Metal Processing, Nancy, France.
  • Rt J.F. (1950): Differential Algebra. New York, American Math. Society.
  • Seliger R. and P.M. Frank. (1991): Robust component fault detection and isolation in nonlinear dynamic systems using nonlinear unknown input observers. Proceedings of the IFAC Symposium SAFEPROCESS'91, Baden-Baden, Germany, pp.313-318.
  • Shumsky, A.Ye. (1991): Fault isolation in nonlinear systems via functional diagnosis. Automation and Remote Control, Vol.52, No.12, pp.1759-1765.
  • Shumsky, A.Ye. (1992): Diagnosis of parametric errors in dynamic objects by the hypothesizes testing method. Avtomatika i telemehanika, Vol.53, No.10, pp.171-177 (in Russian).
  • Shumsky, A.Ye. (2002): Robust analytical redundancy relations for fault diagnosis in nonlinear systems. Asian Journal of Control, Vol.4, No2, pp.159-170.
  • Shumsky, A. Ye. and A. N. Zhirabok. (2006): Nonlinear diagnostic filter design: Algebraic and geometric points of view. International Journal of Applied Mathematics and Computer Science, Vol.16, No.1, pp.115-127.
  • Shumsky, A. Ye. (2006): Fault diagnosis of sensors in autonomous underwater vehicle: Adaptive quasi-linear parity relations method. Proceedings of the International Symposium SAFEPROCESS, Beijing, PR China, pp.415-520
Typ dokumentu
Bibliografia
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Identyfikator YADDA
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