A method for estimating the characteristics of digital models of cyber-physical systems based on multiple regression analysis of the results of their application


DOI: 10.34759/trd-2023-131-19

Аuthors

Minakov E. P.*, Privalov A. E.*, Bugaichenko P. Y.*

Mlitary spaсe Aсademy named after A.F. Mozhaisky, Saint Petersburg, Russia

*e-mail: vka@mil.ru

Abstract

Digital technologies implementation in the sphere of complex technical systems control has led to the advent of the cyber-physical systems (CPS) concepts and digital twins (DT). The DT basic element is the digital model (DM) of the CPS. Requirements to the DM characteristics are being confirmed while tests, verification and validation, to which ensuring the problems of substantiating the list of the DM characteristics and developing methods for their assessment are being solved. The article substantiates the choice of completeness and veracity of the DM as its target characteristics. A method for their assessment by the characteristics of the accuracy of the of the CPS properties estimates obtained with the DM, and the weighting coefficients determined employing multiple regression analysis of the DM application results is proposed. The said method is based on the analysis of the CPS target function, due to which the criterion applied in assessing veracity receives an obvious physical meaning. The proposed method may be employed for solving the problems of the DT structural and parametric synthesis, as well as analyzing their functioning effectiveness at all stages of the CPS life cycle. The result of the training stage is analytical models of the CPS characteristics, which can be used in optimization algorithms without significant requirements for computing resources. The training sample can be replenished while the DT exploitation which increases the accuracy of the DM characteristics assessment at various stages of the CPS life cycle. The adequacy of the method is confirmed by the presented in the article example of the DM characteristics evaluating of an angular motion control system with flywheel engines.

Keywords:

digital model, digital twin, qualimetry of models, multiple regression analysis

References

  1. Sistemy iskusstvennogo intellekta. Klassifikatsiya sistem iskusstvennogo intellekta. GOST R 59277–2020. (Artificial intelligence systems. Classification of artificial intelligence systems, State Standart R 59277–2020), Moscow, Standartinform, 2021, 16 p.
  2. Dorozhko I.V., Gorokhov I.A., Kirillov I.A. Trudy MAI, 2022, no. 125. URL: https://trudymai.ru/eng/published.php?ID=168195. DOI: 34759/trd-2022-125-23
  3. Matveev A.V., Makhukov A.A. Trudy MAI, 2011, no. 45. URL: https://trudymai.ru/eng/published.php?ID=25461
  4. Kabanov A.A., Amosov M.V. Trudy MAI, 2023, no. 128. URL: https://trudymai.ru/eng/published.php?ID=171410
  5. Shchekochikhin O.V. Informatsionno-ekonomicheskie aspekty standartizatsii i tekhnicheskogo regulirovaniya, 2021, no. 5 (63), pp. 33–37.
  6. Mozokhin A.E., Shvedenko V.N. Nauchno-tekhnicheskii vestnik informatsionnykh tekhnologii, mekhaniki i optiki, 2023, vol. 23, no. 2, pp. 289–298.
  7. Cai Y., Starly B., Cohen P., Lee Y-S. Sensor data and information fusion to construct digital-twins virtual machine tools for cyber-physical manufacturing, Procedia Manufacturing, 2017, no. 2, pp. 1031–1042. DOI: 1016/j.promfg.2017.07.094
  8. Tao F., Qi Q., Wang L., Nee A.Y.C. Digital Twins and Cyber—Physical Systems toward Smart Manufacturing and Industry 4.0: Correlation and Comparison, Engineering, 2019, vol. 5, issue 4, pp. 653–661. DOI: 1016/j.eng.2019.01.014
  9. Gusev P.Yu. Avtomatizatsiya planirovaniya proizvodstvennykh protsessov aviastroitel’nogo predpriyatiya s ispol’zovaniem tsifrovogo dvoinika, Trudy MAI, 2018, no. 103. URL: https://trudymai.ru/eng/published.php?ID=101190
  10. Komp’yuternye modeli i modelirovanie. Tsifrovye dvoiniki izdelii. Obshchie polozheniya, GOST R 57700.37–2021 (Computer models and modeling. Digital twins of products. General provisions, State Standart R 57700.37–2021), Moscow, Rossiiskii institut standartizatsii, 2021, 16 p.
  11. Shmelev V.V., Okhtilev M.Yu. Informatsionno-upravlyayushchie sistemy, 2016, no. 6, pp. 34–42.
  12. Mikoni S.V., Sokolov B.V., Yusupov R.M. Kvalimetriya modelei i polimodel’nykh kompleksov: monografiya. (Qualimetry of models and polymodel complexes: monograph), Moscow, RAN, 2018, 314 p.
  13. Mikoni S.V., Sokolov B.V., Yusupov R.M. Shestaya vserossiiskaya nauchno-prakticheskaya konferentsiya po imitatsionnomu modelirovaniyu i ego primeneniyu v nauke i promyshlennosti «Imitatsionnoe modelirovanie. Teoriya i praktika (IMMOD 2013)»: sbornik dokladov, Kazan’, Izd-vo FEN, 2013, pp. 68–79.
  14. Chueva E.S. XXI Mezhdunarodnaya konferentsiya po myagkim vychisleniyam i izmereniyam: sbornik trudov. Saint Petersburg, Izd-vo LETI, 2018, vol. 2, pp. 529–532.
  15. Bun’kova D.E. Ekonomika i upravlenie: problemy, resheniya, 2019, vol. 4, no. 3, pp. 150–159.
  16. Gusarova N.F. Vvedenie v teoriyu iskusstvennogo intellekta (Introduction to the theory of artificial intelligence), Saint Petersburg, Universitet ITMO, 2018, 62 p.
  17. Kremer N.Sh. Teoriya veroyatnostei i matematicheskaya statistika (Theory of probability and mathematical statistics), Moscow, Izd-vo Yuniti-Dana, 2004, 573 p.
  18. Glaessgen E.H., Stargel D.S. The Digital Twin Paradigm forFuture NASA and U.S. Air Force Vehicles, Paper for the 53rd Structures, Structural Dynamics, and Materials Conference: Special Session on the Digital Twin, 2012. DOI:2514/6.2012-1818
  19. Christofi N., Pucel X. A Novel Methodology to Construct Digital Twin Models for Spacecraft Operations Using Fault and Behaviour Trees, 25th International Conference on Model Driven Engineering Languages and Systems (MODELS ’22 Companion), October 23–28, 2022, Montreal. DOI: 1145/3550356.3561550
  20. Potyupkin A.Yu. VIII Mezhdunarodnaya konferentsiya i molodezhnaya shkola «Informatsionnye tekhnologii i nanotekhnologii», ITNT-2022, Samara, Samarskii natsional’nyi issledovatel’skii universitet im. akad. S.P. Koroleva, 2022, 107 p.
  21. Privalov A.E. Trudy MAI, 2022, no. 123. URL: https://trudymai.ru/eng/published.php?ID=165498. DOI: 34759/trd-2022-123-22
  22. Vasil’ev V.N. Sistemy orientatsii kosmicheskikh apparatov (Spacecraft attitude control systems), Moscow, NPP VNIIEM, 2009, 310 p.
  23. Kalabin P.V., Stepanov A.S., Fominov I.V. Trudy Voenno-kosmicheskoi akademii imeni A. F. Mozhaiskogo, 2022, no. 683, pp. 57–66.

Download

mai.ru — informational site MAI

Copyright © 2000-2024 by MAI

 Вход