Skip to main content
SpringerLink
Log in

Virtual Sensors for Discrete-Time Nonlinear Systems

  • Published:
Measurement Techniques Aims and scope

The problem of virtual sensor design is described for a given technical system equipped with sensors to measure the components of its state vector. Such sensors can be useful in cases where existing physical sensors are insufficient or a failed sensor needs to be replaced. The use of additional physical sensors to achieve the necessary result may require extra costs; in addition, the reliability of such sensors is usually low. The authors state and solve the problem of designing virtual sensors for technical systems described by dynamic models representing nonsmooth nonlinearities (dry friction, play, hysteresis, and saturation) under external perturbations. Relations are presented that enable the design of a sensor of minimum complexity that can estimate given state vector components of the system. A sensor synthesized in this way will be insensitive or minimally sensitive to external perturbations and can complement existing physical sensors or replace a failed physical sensor. Theoretical principles are illustrated using the design of virtual sensors for a known three-tank system as an example. The conducted Matlab-based simulation confirms the accuracy of computations and design. The obtained results can be applied in the design of fault-tolerant systems.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.

Similar content being viewed by others

References

  1. A. N. Zhirabok and Ir. Kim Chkhun, J. Comput. Syst. Sci. Int., 61, 38–46 (2022), https://doi.org/10.1134/S1064230722010130.

  2. A. N. Zhirabok, A. V. Zuev, A. A. Protsenko, and Ir. Kim Chkhun, Meas. Tech., 65, No. 6, 405–411 (2022), https://doi.org/10.1007/s11018-022-02097-2.

  3. M. Witczak, Fault Diagnosis and Fault-Tolerant Control Strategies for Non-Linear Systems, Berlin, Springer (2014),https://doi.org/10.1007/978-3-319-03014-2

  4. Q. Ahmed, A. Bhatti, and M. Iqbal, IEEE Sens. J., 11, No. 9, 1832–1840 (2011), https://doi.org/10.1109/JSEN.2011.2105471.

  5. G. Heredia and A. Ollero, Sensors, 10, 2188–2201 (2010), https://doi.org/10.3390/s100302188.

    Article  ADS  Google Scholar 

  6. Z. Hosseinpoor, M. Arefi, R. Razavi-Far, N. Mozafari, and S. Hazbavi, IEEE Sens. J., 21, No. 4, 5044–5051 (2021), https://doi.org/10.1109/JSEN.2020.3033754.

  7. E. Jove, J. Casteleiro-Roca, H. Quntian, J. Mendez-Perez, and J. Calvo-Rolle, Informatica, 30, No. 4, 671–687 (2019), https://doi.org/10.15388/Informatica.2019.224.

  8. M. Blanke, M. Kinnaert, J. Lunze, and M. Staroswiecki, Diagnosis and Fault-Tolerant Control, Berlin, Springer-Verlag (2006),https://doi.org/10.1007/978-3-540-35653-0

  9. A. Zhirabok and A. Shumsky, Algebraicheskie Metody Analiza Nelinejnyh Dinamicheskih Sistem, Vladivostok, Dalnauka Publ., 2008.

  10. G. Gratzer, General Lattice Theory, Akademie, Berlin (1978).

    Book  MATH  Google Scholar 

  11. J. Belikov, A. Kaldmae, V. Kaparin, U. Kotta, A. Shumsky, M. Tonso, and A. Zhirabok, Proc. Est. Acad. Sci., 66, No. 1, 89–107 (2017), https://doi.org/10.3176/proc.2017.1.06.

    Article  MathSciNet  Google Scholar 

  12. A. Kaldmae, U. Kotta, B. Jiang, A. Shumsky, and A. Zhirabok, Asian J. Control., 8, No. 3, 858–867 (2016), https://doi.org/10.1002/asjc.1185.

    Article  Google Scholar 

  13. E. Misawa and J. Hedrick, J. Dyn. Syst. Meas. Control, 111, 344–352 (1989), https://doi.org/10.1115/1.3153059.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Marine Technology Problems, Far East Branch, Russian Academy of Sciences, Vladivostok, Russia

    A. N. Zhirabok & A. V. Zuev

  2. Far Eastern Federal University, Vladivostok, Russia

    A. N. Zhirabok, A. V. Zuev & A. E. Shumsky

Authors
  1. A. N. Zhirabok
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. V. Zuev
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A. E. Shumsky
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. N. Zhirabok.

Additional information

Translated from Izmeritel’naya Tekhnika, No. 4, pp. 18–22, April, 2023. https://doi.org/10.32446/0368-1025it.2023-4-18-22.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhirabok, A.N., Zuev, A.V. & Shumsky, A.E. Virtual Sensors for Discrete-Time Nonlinear Systems. Meas Tech 66, 231–236 (2023). https://doi.org/10.1007/s11018-023-02215-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11018-023-02215-8

Keywords

Search

Navigation