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Identification of Faults in Nonlinear Dynamical Systems and Their Sensors Based on Sliding Mode Observers

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Abstract

We consider the problem of fault identification in nonlinear technical systems described by dynamic models and in their sensors in the presence of disturbances. A method based on sliding mode observers is used to solve the problem. A modification of this method is proposed which permits one to expand the family of systems for which the identification problem can be solved by weakening the constraints imposed on the original system. This modification has made it possible to reduce the complexity of diagnostic tools. The results are illustrated by practical examples.

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REFERENCES

  1. Zhirabok, A., Zuev, A., and Shumsky, A., Diagnosis of linear dynamic systems: an approach based on sliding mode observers, Autom. Remote Control, 2020, vol. 81, no. 2, pp. 211–225.

    Article  MathSciNet  Google Scholar 

  2. Utkin, V.I., Skol’zyashchie rezhimy i ikh primenenie v sistemakh s peremennoi strukturoi (Sliding Modes and Their Application in Systems with Variable Structure), Moscow: Nauka, 1974.

    Google Scholar 

  3. Korovin, S.K. and Fomichev, V.V., Nablyudateli sostoyaniya dlya lineinykh sistem s neopredelennost’yu (State Observers for Linear Systems with Uncertainty), Moscow: Fizmatlit, 2007.

    Google Scholar 

  4. Krasnova, S.A. and Kuznetsov, S.I., Uncontrollable perturbation of nonlinear dynamic systems: estimation on moving modes, Autom. Remote Control, 2005, vol. 66, no. 10, pp. 1580–1593.

    Article  MathSciNet  Google Scholar 

  5. Krasnova, S.A. and Utkin, V.A., Kaskadnyi sintez nablyudatelei sostoyaniya dinamicheskikh sistem (Cascade Synthesis of State Observers of Dynamical Systems), Moscow: Nauka, 2006.

    Google Scholar 

  6. Shtessel, Yu., Edwards, C., Fridman, L., and Levant, A., Sliding Mode Control and Observation, New York: Springer, 2014.

    Book  Google Scholar 

  7. Fridman, L., Levant, A., and Davila, J., Observation of linear systems with unknown inputs via high order sliding modes, Int. J. Syst. Sci., 2007, vol. 38, pp. 773–791.

    Article  MathSciNet  Google Scholar 

  8. Edwards, C., Spurgeon, S., and Patton, R., Sliding mode observers for fault detection and isolation, Automatica, 2000, vol. 36, pp. 541–553.

    Article  MathSciNet  Google Scholar 

  9. Kalsi, K., Hui, S., and Zak, S., Unknown input and sensor fault estimation using sliding-mode observers, Proc. 2011 ACC (San Francisco, 2011), pp. 1364–1369.

  10. Yan, X. and Edwards, C., Nonlinear robust fault reconstruction and estimation using a sliding modes observer, Automatica, 2007, vol. 43, pp. 1605–1614.

    Article  MathSciNet  Google Scholar 

  11. He, J. and Zhang, C., Fault reconstruction based on sliding mode observer for nonlinear systems, in Mathematical Problems in Engineering, 2012, pp. 1–22.

  12. Tan, C. and Edwards, C., Sliding mode observers for robust detection and reconstruction of actuator and sensor faults, Int. J. Robust Nonlinear Control, 2003, vol. 13, pp. 443–463.

    Article  MathSciNet  Google Scholar 

  13. Brahim, A., Dhahri, S., Hmida, F., and Sellami, A., Simultaneous actuator and sensor faults reconstruction based on robust sliding mode observer for a class of nonlinear systems, Asian J. Control, 2017, vol. 19, pp. 362–371.

    Article  MathSciNet  Google Scholar 

  14. Chang, J., Tan, C., Trinh, H., and Kamal, M., State and fault estimation for a class of non-infinitely observable descriptor systems using two sliding mode observers in cascade, J. Franklin Inst., 2019, vol. 356, pp. 3010–3029.

    Article  MathSciNet  Google Scholar 

  15. Castillo, I., Fridman, L., and Moreno, J., Super-twisting algorithm in presence of time and state dependent perturbations, Int. J. Control, 2018, vol. 91, pp. 2535–2548.

    Article  MathSciNet  Google Scholar 

  16. Mironovskii, L.A., Funktsional’noe diagnostirovanie dinamicheskikh sistem (Functional Diagnostics of Dynamical Systems), Moscow–St. Petersburg: Izd. Mosk. Gos. Univ.–GRIF, 1998.

    Google Scholar 

  17. Zhirabok, A., Shumsky, A., and Zuev, A., Fault diagnosis in linear systems via sliding mode observers, Int. J. Control, 2021, vol. 94, no. 2, pp. 327–335.

    Article  MathSciNet  Google Scholar 

  18. Zhirabok, A., Shumsky, A., Solyanik, S., and Suvorov, A., Fault detection in nonlinear systems via linear methods, Int. J. Appl. Math. Comput. Sci., 2017, vol. 27, pp. 261–272.

    Article  MathSciNet  Google Scholar 

  19. Zhirabok, A., Shumsky, A., and Pavlov, S., Diagnosis of linear dynamic systems by the nonparametric method, Autom. Remote Control, 2017, vol. 78, no. 7, pp. 1173–1188.

    Article  MathSciNet  Google Scholar 

  20. Zhirabok, A.N., Shumsky, A.E., and Zuev, A.V., Diagnosis of linear systems based on sliding mode observers, J. Comput. Syst. Sci. Int., 2019, vol. 58, no. 6, pp. 898–914.

    Article  Google Scholar 

  21. Zuev, A.V. and Filaretov, V.F., Features of designing combined force/position manipulator control systems, J. Comput. Syst. Sci. Int., 2009, vol. 48, no. 1, pp. 146–154.

    Article  MathSciNet  Google Scholar 

  22. Emel’yanov, S.V., Sistemy avtomaticheskogo upravleniya s peremennoi strukturoi (Automatic Control Systems with Variable Structure), Moscow: Nauka, 1967.

    Google Scholar 

  23. Blanke, M., Kinnaert, M., Lunze, J., and Staroswiecki, M., Diagnosis and Fault-Tolerant Control, Berlin: Springer-Verlag, 2006.

    MATH  Google Scholar 

  24. Witczak, M., Fault Diagnosis and Fault Tolerant Control Strategies for Nonlinear Systems, Berlin: Springer, 2014.

    Book  Google Scholar 

  25. Zhirabok, A.N. and Kim Chkhun Ir, Virtual sensors in the fault diagnosis problem, Mekhatron. Avtom. Upr., 2021, no. 6, pp. 298–303.

  26. Filaretov, V.F., Samonastraivayushchiesya sistemy upravleniya privodami manipulyatorov (Self-Adjusting Manipulator Drive Control Systems), Vladivostok: Izd. DVGTU, 2000.

    Google Scholar 

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Funding

This work was supported by the Russian Foundation for Basic Research, projects nos. 22-19-00028 (method of sliding mode observers design) and 22-29-01303 (synthesis of sliding mode observers).

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Authors and Affiliations

  1. Far Eastern Federal University, Vladivostok, 690090, Russia

    A. N. Zhirabok & A. E. Shumsky

  2. Institute of Marine Technology Problems, Far-East Branch, Russian Academy of Sciences, Vladivostok, 690091, Russia

    A. N. Zhirabok & A. V. Zuev

  3. Universidad Autonoma de Baja California, Mexicali, 21100, Mexico

    O. Sergiyenko

Authors
  1. A. N. Zhirabok
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  2. A. V. Zuev
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  3. O. Sergiyenko
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  4. A. E. Shumsky
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Corresponding authors

Correspondence to A. N. Zhirabok, A. V. Zuev, O. Sergiyenko or A. E. Shumsky.

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Translated by V. Potapchouck

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Zhirabok, A.N., Zuev, A.V., Sergiyenko, O. et al. Identification of Faults in Nonlinear Dynamical Systems and Their Sensors Based on Sliding Mode Observers. Autom Remote Control 83, 214–236 (2022). https://doi.org/10.1134/S0005117922020059

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  • DOI: https://doi.org/10.1134/S0005117922020059

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