Advertisement

Numerical Modeling of Dynamic Disturbances Acting on the Sensitive Elements of an Instrument Navigation System

  • Igor KorobiichukEmail author
  • Olena Bezvesilna
  • Yuriy Podchashinskiy
  • Katarzyna Rzeplińska-Rykała
Conference paper
  • 80 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1140)

Abstract

The numerical methods for modeling dynamic disturbances that influence a sensitive element (accelerometer) of the instrument navigation system were considered. Algorithms of reproduction of dynamic disturbances on a digital computer with a given correlation function were developed. In the paper presented the results of the studies of numerical modeling of dynamic disturbances in the instrument navigation system with acceptable reproduction accuracy of the statistical characteristics of these disturbances.

Keywords

Dynamic disturbances Correlation function Instrument navigation system Accelerometer 

References

  1. 1.
    Bezvesilna, O.M.: Measuring Acceleration: Tutorial. Libid: Kyiv, 264 p. (2001)Google Scholar
  2. 2.
    Bezvesilna, O.M.: Aviation gravimetric systems and gravimeters. ZhSTU: Zhytomyr, 604 p. (2007)Google Scholar
  3. 3.
    Korobiichuk, I., Bezvesilna, O., Tkachuk, A., Chilchenko, T., Nowicki, M., Szewczyk, R.: Design of piezoelectric gravimeter for automated aviation gravimetric system. J. Autom. Mob. Robot. Intell. Syst. 10(1), 43–47 (2016).  https://doi.org/10.14313/JAMRIS_1-2016/6CrossRefGoogle Scholar
  4. 4.
    Bezvesilna, O., Korobiichuk, I., Nechai, J., Podchashynskyi, Yu.: Gravity meter, Patent UA78620 (C2) (2007)Google Scholar
  5. 5.
    Korobiichuk, I., Nowicki, M., Szewczyk, R.: Design of the novel double-ring dynamical gravimeter. J. Autom. Mob. Robot. Intell. Syst. 9(3), 47–52 (2015).  https://doi.org/10.14313/jamris_3-2015/23CrossRefGoogle Scholar
  6. 6.
    Korobiichuk, I., Podchashinskiy, Yu., Bezvesilna, O., Nechay, S., Shavurskiy, Yu.: Three-coordinate gravimeter with exhibition of axis sensitivity based on digital videoimages. In: Proceeding ICIGP 2019 Proceedings of the 2nd International Conference on Image and Graphics Processing, Singapore, pp. 89–93 (2019).  https://doi.org/10.1145/3313950.3314187
  7. 7.
    Korobiichuk, I.: Mathematical model of precision sensor for an automatic weapons stabilizer system. Measurement 89, 151–158 (2016).  https://doi.org/10.1016/j.measurement.2016.04.017CrossRefGoogle Scholar
  8. 8.
    Ermakov, S.M.: Monte Carlo Method and Related Issues. Science, Moskva, 472 p. (1975)Google Scholar
  9. 9.
    Chen, D., Zhou, N., Li, C., Guo, H., Cui, T.: A dynamic power flow model considering the uncertainty of primary frequency regulation of system. Adv. Intell. Syst. Comput. 902, 425–438 (2020).  https://doi.org/10.1007/978-3-030-12082-5_39Google Scholar
  10. 10.
    Baltagi, B.H., Fingleton, B., Pirotte, A.: A time-space dynamic panel data model with spatial moving average errors. Reg. Sci. Urban Econ. 76, 13–31 (2019).  https://doi.org/10.1016/j.regsciurbeco.2018.04.013CrossRefGoogle Scholar
  11. 11.
    Hendricks, E., Jannerup, O., Sørensen, P.H.: Linear systems control: deterministic and stochastic methods, 555 p. (2008).  https://doi.org/10.1007/978-3-540-78486-9
  12. 12.
    Tomashevsky, V.M.: Systems Modeling: A Tutorial, p. 352. BHV, Kyiv (2005)Google Scholar
  13. 13.
    Rohani, S., Wu, Y.: Theoretical Process Dynamic Modeling. Coulson and Richardson’s Chemical Engineering: Vol. 3B: Process Control, pp. 39–94 (2017).  https://doi.org/10.1016/b978-0-08-101095-2.00003-5CrossRefGoogle Scholar
  14. 14.
    Lu, C.X., Rees, N.W., Young, P.C.: Simulation model emulation in control system design. In: System Identification, Environmental Modelling, and Control System Design, 9781430237051, pp. 583–597 (2013).  https://doi.org/10.1007/978-0-85729-974-1_28CrossRefGoogle Scholar
  15. 15.
    Shalygin, A.S., Palagin, Yu.I.: Applied methods of statistical modeling. Mechanical Engineering: Lviv, 320 p. (1986)Google Scholar
  16. 16.
    Schabenberger, O., Gotway, C.A.: Statistical methods for spatial data analysis, 488 p. (2017).  https://doi.org/10.1201/9781315275086CrossRefGoogle Scholar
  17. 17.
    Bykov, V.V.: Digital Modeling in Statistical Radio Engineering, 326 p. Soviet Radio, Moscow (1971)Google Scholar
  18. 18.
    Verdugo Muñoz, E., Da Silva Mello, L., Almeida, M.P.C.: Results of medium wave HD radio mobile reception measurements in a dense urban region. In: IET Conference Publications (2018). CP741Google Scholar
  19. 19.
    Saadoune, N., Radi, B.: Probabilistic study an embedded system. In: Colloquium in Information Science and Technology, CIST, art. no. 7804988, pp. 756–761 (2017).  https://doi.org/10.1109/cist.2016.7804988
  20. 20.
    Korobiichuk, I.: Automatic control devices. Ed. PIAP: Warsaw, p. 104 (2018). ISBN 978-83-61278-34-4Google Scholar
  21. 21.
    Korobiichuk, I., et al.: Synthesis of optimal robust regulator for food processing facilities. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds.) Automation 2017. ICA 2017. Advances in Intelligent Systems and Computing, vol. 550. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-54042-9_5CrossRefGoogle Scholar
  22. 22.
    Padoan, A., Astolfi, A.: Moments of random variables: a system-theoretic interpretation. In: Proceedings of the American Control Conference, art. no. 7963089, pp. 1035–1040 (2017).  https://doi.org/10.23919/acc.2017.7963089
  23. 23.
    Vargas, R.E.: Fuzzy logic: theory, programming and applications, pp. 1–448 (2010)Google Scholar
  24. 24.
    Volos, C., Stouboulos, I., Kyprianidis, I., Vaidyanathan, S.: Design of a chaotic random bit generator using a Duffing – van der Pol system. In: Artificial Intelligence: Concepts, Methodologies, Tools, and Applications, vol. 2, pp. 841–860 (2016).  https://doi.org/10.4018/978-1-5225-1759-7.ch034

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Igor Korobiichuk
    • 1
    Email author
  • Olena Bezvesilna
    • 2
  • Yuriy Podchashinskiy
    • 3
  • Katarzyna Rzeplińska-Rykała
    • 4
  1. 1.Institute of Automatic Control and RoboticsWarsaw University of TechnologyWarsawPoland
  2. 2.National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”KievUkraine
  3. 3.Zhytomyr State Technological UniversityZhytomyrUkraine
  4. 4.ŁUKASIEWICZ Research Network – Industrial Research Institute for Automation and Measurements PIAPWarsawPoland

Personalised recommendations