Fault Identification: An Approach Based on Optimal Control Methods

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Abstract

This paper considers the problem of identifying (estimating) faults in systems described by linear models under exogenous disturbances. It is solved using optimal control methods; in comparison with sliding mode observers, they avoid high-frequency switching. The solution method proposed below involves a reduced model of the original system that is sensitive to faults and insensitive to disturbances. The corresponding theory is illustrated by an example.

About the authors

A. A. Kabanov

Sevastopol State University

Email: kabanovaleksey@gmail.com
Sevastopol, Russia

A. V. Zuev

Far Eastern Federal University; Institute of Marine Technology Problems, Far Eastern Branch, Russian Academy of Sciences

Email: alvzuev@yandex.ru
Vladivostok, Russia; Vladivostok, Russia

A. N. Zhirabok

Far Eastern Federal University; Institute of Marine Technology Problems, Far Eastern Branch, Russian Academy of Sciences

Email: zhirabok@mail.ru
Vladivostok, Russia; Vladivostok, Russia

V. F. Filaretov

Institute of Automation and Control Processes, Far Eastern Branch, Russian Academy of Sciences

Author for correspondence.
Email: filaretov@inbox.ru
Vladivostok, Russia

References

  1. Edwards C., Spurgeon S., Patton R. Sliding mode observers for fault detection and isolation // Automatica. 2000. V. 36. P. 541-553.
  2. Floquet T., Barbot J., Perruquetti W., Djemai M. On the robust fault detection via a sliding mode disturbance observer // Int. J. Control. 2004. V. 77. P. 622-629.
  3. Yan X., Edwards C. Nonlinear robust fault reconstruction and estimation using a sliding modes observer // Automatica. 2007. V. 43. P. 1605-1614.
  4. Rios H., E mov D., Davila J., Raissi T., Fridman L., Zolghadri A. Non-minimum phase switched systems: HOSM based fault detection and fault identi cation via Volterra integral equation // Int. J. Adapt. Contr. and Signal Proc. 2014. V. 28. P. 1372-1397.
  5. Жирабок А.Н., Зуев А.В., Филаретов В.Ф., Шумский А.Е. Идентификация дефектов в нелинейных системах на основе скользящих наблюдателей с ослабленными условиями существования // Изв. РАН. ТиСУ. 2022. № 3. С. 21-30.
  6. Жирабок А.Н., Зуев А.В., Сергиенко О., Шумский А.Е. Идентификация дефектов в нелинейных динамических системах и их датчиках на основе скользящих наблюдателей // АиТ. 2022. № 2. С. 63-89.
  7. Жирабок А.Н., Зуев А.В., Шумский А.Е. Методы идентификации и локализации дефектов в линейных системах на основе скользящих наблюдателей // Изв. РАН. ТиСУ. 2019. № 6. С. 73-89.
  8. Мироновский Л.А. Функциональное диагностирование динамических систем. М.; СПб.: МГУ-ГРИФ, 1998.
  9. Hautus M. Strong detectability and observers // Linear Algebra and its Applications. 1983. V. 50. P. 353-368.
  10. Корн Г., Корн Т. Справочник по математике. М.: Наука, 1968.
  11. Mufti I.H., Chow C.K., Stock F.T. Solution of ill-conditioned linear two-point boundary value problems by the Riccati transformation // SIAM Rev. 1969. V. 11. No. 4. P. 616-619.
  12. Naidu D.S. Optimal control systems. Electrical Engineering Handbook, Florida, Boca Raton: CRC Press, 2003. 275 p.
  13. Брайсон А., Хо Ю-ши. Прикладная теория оптимального управления. М.: Мир, 1972. 544 с.
  14. Квакернаак Х., Сиван Р. Линейные оптимальные системы управления. M.: Миp, 1977. 652 с.
  15. Kim S., Kwon S.J. Nonlinear optimal control design for underactuated two-wheeled inverted pendulum mobile platform // IEEE/ASME Transactions on Mechatronics. 2017. V. 22. No. 6. P. 2803-2808.

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