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Helicopters Turboshaft Engines Parameters Identification Using Neural Network Technologies Based on the Kalman Filter

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Information and Communication Technologies in Education, Research, and Industrial Applications (ICTERI 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1980))

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Abstract

The work is a continuation of the research devoted to the development of a multidimensional Kalman filter connected at the output of the built-in helicopter’s turboshaft engines mathematical dynamic model to improve the accuracy of helicopters turboshaft engines parameters identification and achieve high quality automatic control. The main difference is the use of radial basis functions neural networks, in which the multivariate Kalman filter is a training algorithm. The work illustrates well-known mathematical expressions underlying of optimal multidimensional filtering algorithms. The methods of mathematical modeling in the Matlab environment tested the proposed algorithms. The simulation results showed that the use of neural networks trained by the multidimensional Kalman matrix filter as part of the model of helicopters turboshaft engines built into the automatic control system allows achieving high indicators of the accuracy of identifying the parameters of helicopters turboshaft engines automatic control system – up to 0.9975, then in practical analogues.

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Author information

Authors and Affiliations

  1. Kremenchuk Flight College of Kharkiv National University of Internal Affairs, Peremohy Street, 17/6, Kremenchuk, 39605, Ukraine

    Serhii Vladov, Yurii Shmelov & Ruslan Yakovliev

  2. Kharkiv National University of Internal Affairs, L. Landau Avenue, 27, Kharkiv, 61080, Ukraine

    Maryna Petchenko

Authors
  1. Serhii Vladov
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  2. Yurii Shmelov
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  3. Ruslan Yakovliev
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  4. Maryna Petchenko
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Corresponding author

Correspondence to Serhii Vladov .

Editor information

Editors and Affiliations

  1. University of Huddersfield, Huddersfield, UK

    Grigoris Antoniou

  2. Ukrainian Catholic University, Lviv, Ukraine

    Vadim Ermolayev

  3. Kherson State University, Kherson, Ukraine

    Vitaliy Kobets

  4. Odessa National Polytechnic University, Odesa, Ukraine

    Vira Liubchenko

  5. University of Klagenfurt, Klagenfurt, Austria

    Heinrich C. Mayr

  6. Kherson State University, Kherson, Ukraine

    Aleksander Spivakovsky

  7. University of Warmia and Mazury in Olsztyn, Olsztyn, Poland

    Vitaliy Yakovyna

  8. V. N. Karazin Kharkiv National University, Kharkiv, Ukraine

    Grygoriy Zholtkevych

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Vladov, S., Shmelov, Y., Yakovliev, R., Petchenko, M. (2023). Helicopters Turboshaft Engines Parameters Identification Using Neural Network Technologies Based on the Kalman Filter. In: Antoniou, G., et al. Information and Communication Technologies in Education, Research, and Industrial Applications. ICTERI 2023. Communications in Computer and Information Science, vol 1980. Springer, Cham. https://doi.org/10.1007/978-3-031-48325-7_7

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  • DOI: https://doi.org/10.1007/978-3-031-48325-7_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-48324-0

  • Online ISBN: 978-3-031-48325-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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