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Articles

Vol. 10 (2023)

Virtual Sensor Design for Replacement the Faulty Physical Sensors

DOI
https://doi.org/10.31875/2409-9694.2023.10.03
Submitted
June 24, 2023
Published
24.06.2023

Abstract

Abstract: The paper considers the problem of virtual sensor design for nonlinear dynamic systems with non-smooth nonlinearities described by continuous-time models for faulty physical sensor replacement. It is assumed that to solve the problem, the system is equipped by diagnostic system allowing detecting and isolating the faulty sensor. For every such a sensor, the virtual sensor generating estimate replacing the faulty sensor is designed. To solve the problem, so-called logic-dynamic approach is used which does not guarantee optimal solution but uses only methods of linear algebra to solve the problem for systems with non-smooth nonlinearities. The virtual sensor can be designed in the identification canonical form or Jordan canonical form. The advantage of the first form is a standard procedure of the virtual sensor design while Jordan form allows obtaining a simpler solution. The relations allowing designing the virtual sensor both in identification and in Jordan canonical form are derived.

References

  1. Blanke M., Kinnaert M., Lunze J., Staroswiecki M. Diagnosis and fault tolerant control, 2016, Berlin: Springer-Verlag. https://doi.org/10.1007/978-3-662-47943-8
  2. Ahmed Q., Bhatti A., Iqbal M. Virtual sensors for automotive engine sensors fault diagnosis in second-order sliding modes, IEEE Sensors J. 2011; 11: 1832-1840. https://doi.org/10.1109/JSEN.2011.2105471
  3. Heredia G., Ollero A. Virtual sensor for failure detection, identification and recovery in the transition phase of a morphing aircraft, Sensors 2010; 10: 2188-2201. https://doi.org/10.3390/s100302188
  4. Hosseinpoor Z., Arefi M., Razavi-Far R., Mozafari N., Hazbavi S. Virtual sensors for fault diagnosis: a case of induction motor broken rotor bar, IEEE Sensors J. 2021; 21: 5044-5051. https://doi.org/10.1109/JSEN.2020.3033754
  5. Misawa E.A., Hedrick J.K. Nonlinear observers - a state of the art survey, J. Dynamic Systems, Measurements and Control 1989; 111; 344-352. https://doi.org/10.1115/1.3153059
  6. Roy C., Roy A., Misra S. DIVISOR: Dynamic virtual sensor formation for overlapping region in IOT-based sensor-cloud, in 2018 IEEE Wireless Communications and Networking Conf., 2018, Barcelona, Spain. https://doi.org/10.1109/WCNC.2018.8377221
  7. Rotondo D., Nejjari F., Puig V. A virtual actuator and sensor approach for fault tolerant control of LPV systems, J. Process Control 2014; 24: 203-222. https://doi.org/10.1016/j.jprocont.2013.12.016
  8. Rotondo D., Ponsart J., Theilliol D., Nejjaria F., Puig V. A virtual actuator approach for the fault tolerant control of unstable linear systems subject to actuator saturation and fault isolation delay, Annual Reviews in Control 2015; 1-31. https://doi.org/10.1016/j.arcontrol.2015.03.006
  9. Wang Y., Rotondo D., Puig V., Cembrano G. Fault tolerant control based on virtual actuator and sensor for discrete-time descriptor systems, IEEE Trans. on Circuits and Systems 2020; 67: 5316-5325. https://doi.org/10.1109/TCSI.2020.3015887
  10. Witczak M. Fault diagnosis and fault tolerant control strategies for nonlinear systems, 2014, Berlin: Springer. https://doi.org/10.1007/978-3-319-03014-2
  11. Zhirabok A., Kim C. Virtual sensors for the functional diagnosis of nonlinear systems, J. Computer and Systems Sciences Int. 2022; 61: 38-46. https://doi.org/10.1134/S1064230722010130
  12. Zhirabok A., Zuev A., Shumsky A. Diagnosis of linear dynamic systems: an approach based on sliding mode observers", Automation and Remote Control 2020; 81: 18-35. https://doi.org/10.1134/S0005117920020022
  13. Zhirabok A. Analysis of observability and controllability of nonlinear dynamic systems by linear methods, J. Computer and Systems Sciences Int. 2010; 49: 10-17. https://doi.org/10.1134/S1064230710010028
  14. Zhirabok A., Zuev A., Filaretov V., Shumsky A., Kim C. Jordan canonical form in the diagnosis and estimation problems, Automation and Remote Control 2022; 83: 1355-1370. https://doi.org/10.1134/S0005117922090028
  15. Zhirabok A., Zuev A., Kim C. Virtual sensor design for linear and nonlinear dynamic systems, Int. J. Robotics and Automation Technology 2022; 9: 106-113. https://doi.org/10.31875/2409-9694.2022.09.10