Research of software package modules for identification of dynamic objects

Authors

DOI:

https://doi.org/10.15587/2312-8372.2015.51740

Keywords:

packages of software modules, identification, dynamic objects, modeling, management, system, model parameters

Abstract

There were researched the packages of software modules for dynamics objects identifying, that were make ability of saving in opposite of simple software modules for automatic forming of applications. The article shows the place of the packages of software modules for checking of dynamics objects identifying on stationary condition and also the ability of using for many times adaptively identifying systems. The package of software module consists of the package core, data base and models, which can be changed according to subjects. The input for software module is the task of identifying of some dynamic object with static information about this object with the time interval. The output is identified dynamic object model and forecast the behavior of this object for the future. The process of creating packages of software modules for dynamics objects identifying should be connected to the subject area, but because of modularity it can be possible to use separated software packages of modules with different subject areas.

Author Biographies

Сергій Віталійович Грибков, National University of Food Technologies, st. Volodymyrska 68, Kyiv, Ukraine, 01601

Candidate of Technical Science

Department of Information Systems

Тетяна Вікторівна Логвин, National University of Food Technologies, st. Volodymyrska 68, Kyiv, Ukraine, 01601

Postgraduate

Department of Information Systems

Олена Валеріївна Харкянен, National University of Food Technologies, st. Volodymyrska 68, Kyiv, Ukraine, 01601

Candidate of Technical Science

Department of Information Systems

References

  1. Diakonov, V., Kruglov, V. (2001). MATLAB. Analiz, identifikatsiia i modelirovanie sistem. St. Petersburg: Piter, 448.
  2. Billings, S. A. (2013, July 23). Severely Nonlinear Systems. NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains. Wiley-Blackwell, 289–336. doi:10.1002/9781118535561.ch9
  3. Samsonov, V. V., Silvestrov, A. M. (2012). Narysy z teorii identyfikatsii. Kyiv: NUKhT, 222.
  4. Radyonov, V. M. (2014). Systema upravlenyia hydrotsyklonom s ydentyfykatsyei parametrov y vyborom optymalnoi modely. Hirnychyi visnyk, 97, 181–184.
  5. Mal'tseva, T. V. (2008). Ob odnom metode postroeniia matematicheskoi modeli lineinogo dinamicheskogo ob’ekta. Molodoi uchenyi, 1, 40–48.
  6. Dorofeiuk, Yu. A. (2010). Strukturnaia identifikatsiia slozhnyh ob’ektov upravleniia na baze metodov kusochnoi approksimatsii. Upravlenie bol'shimi sistemami, 30, 79–88.
  7. Ali Hussein Hasan, Grachev, A. N. (2014). On-Line Parameters Estimation Using Fast Genetic Algorithm. Journal of Electrical and Control Engineering (JECE), Vol. 4, 2, 16–21.
  8. Razali, N. M., Geraghty, J. (2011). Genetic Algorithm Performance with Different Selection Strategies in Solving TSP. Proceedings of the World Congress on Engineering, Vol. II. London: UK, 6.
  9. Karpov, A. A., Katsiuba, O. A. (2009). Opredelenie parametrov mnogomernoi po vhodu i vyhodu lineinoi dinamicheskoi sistemy pri nalichii avtokorrelirovannyh pomeh v signalah. Vestnik Samarskogo gosudarstvennogo aerokosmicheskogo universiteta im. ak. S. P. Koroleva, 2 (18), 135–142.
  10. Kalman, R. (1960). Contribution to the Theory of Optimal Control. Bull. Soc. Mat. Mech, Vol. 5, № 1, 102–119. Available: http://liberzon.csl.illinois.edu/teaching/kalman_paper.pdf
  11. Luenberger, D. (1979). Introduction to dynamic systems. N. Y.:Wiley, 446. Available: http://home.deib.polimi.it/guariso/BAC/Texts/Luenberger.pdf

Published

2015-09-22

How to Cite

Грибков, С. В., Логвин, Т. В., & Харкянен, О. В. (2015). Research of software package modules for identification of dynamic objects. Technology Audit and Production Reserves, 5(2(25), 45–49. https://doi.org/10.15587/2312-8372.2015.51740

Issue

Section

Information Technologies: Original Research