Izvestiya of Saratov University.

Mathematics. Mechanics. Informatics

ISSN 1816-9791 (Print)
ISSN 2541-9005 (Online)


For citation:

Andreichenko D. K., Andreichenko K. P., Batraeva I. A. Hybrid Automation Extended Model. Izvestiya of Saratov University. Mathematics. Mechanics. Informatics, 2019, vol. 19, iss. 1, pp. 94-104. DOI: 10.18500/1816-9791-2019-19-1-94-104, EDN: SXOWKY

This is an open access article distributed under the terms of Creative Commons Attribution 4.0 International License (CC-BY 4.0).
Published online: 
28.02.2019
Full text:
(downloads: 152)
Language: 
English
Heading: 
Article type: 
Article
UDC: 
519.713.8 : 517.935.2
EDN: 
SXOWKY

Hybrid Automation Extended Model

Autors: 
Andreichenko Dmitry Konstantinovich, Saratov State University
Andreichenko Konstantin Petrovich, Moscow Aviation Institute (National Research University)
Batraeva Inna A., Saratov State University
Abstract: 

An extended model of hybrid automata for dynamic systems is considered, where, along with a discrete control subsystem and control objects with lumped parameters, there are control objects with distributed parameters (linear and stationary from the point of view of automatic control theory). The possibility of software implementation of an extended model of hybrid automata on embedded computing systems is shown.

References: 
  1. Kashevnik A. M., Ponomarev A. V., Savosin S. V. Hybrid Systems Control Based on Smart Space Technology. SPIIRAS Proceedings, 2014, iss. 4(35), pp. 212–226 (in Russian).
  2. Meslem N., Ramdani M., Candau Y. Guaranteed Parameter Set Estimation for Monotone Dynamical Systems Using Hybrid Automata. In: Reliable Computing, Springer Verlag, 2010, pp. 88–104.
  3. Karoui M. F., Alla H., Chatti A. Monitoring of dynamic processes by rectangular hybrid automata. Nonlinear Analysis: Hybrid Systems, 2010, vol. 4, iss. 4, pp. 766–774. DOI: https://doi.org/10.1016/j.nahs.2010.05.004
  4. Thiagarajan P. S., Yang S. Modular discrete time representation of distributed hybrid automata. Theoretical Computer Science, 2012, vol. 429, pp. 292–304. DOI: https://doi.org/10.1016/j.tcs.2011.12.050
  5. Kone´ cn´ y M., Taha W., Bartha F. A., Duracz J., Duracz A., Ames A. D. Enclosing the behavior of a hybrid automation up to and beyond a Zeno point. Nonlinear Analysis: Hybrid Systems, 2016, vol. 20, pp. 1–20. DOI: https://doi.org/10.1016/j.nahs.2015.10.004
  6. Elmetennani S., Laleg-Kirati T.M., Djemai M., Tadjine M. New MPPT algorithm for PV applications based on hybrid dynamical approach. Journal of Process Control, 2016, vol. 48, pp. 14–24. DOI: https://doi.org/10.1016/j.jprocont.2016.10.001
  7. Iovine A., Valentini F., De Santis E., Di Benedetto M. D., Pratesi M. Safe human-inspired mesoscopic hybrid automation for autonomous vehicles. Nonlinear Analysis: Hybrid Systems, 2017, vol. 25, pp. 192–210. DOI: https://doi.org/10.1016/j.nahs.2016.08.008
  8. Shornikov Yu., Bessonov A., Dostovalov D. Specification and instrumental analysis of hybrid systems. Science Bulletin of the Novosibirsk State Technical University, 2015, no. 4(61), pp. 101–117 (in Russian). DOI: http://dx.doi.org/10.17212/1814-1196-2015-4-101-117
  9. Andreichenko D. K., Andreichenko K. P. On the theory of hybrid dynamical systems. Journal of Computer and Systems Sciences International, 2000, vol. 39, no. 3, pp. 383–398.
  10. Portenko M. S., Melnichuk D. V., Andreichenko D. K. Analyticity conditions of characteristic and disturbing quasipolynomials of hybrid dynamical systems. Izv. Saratov Univ. (N. S.), Ser. Math. Mech. Inform., 2016, vol. 16, no. 2, pp. 208–217 (in Russian). DOI: https://doi.org/10.18500/1816-9791-2016-16-2-208-217
Received: 
21.10.2018
Accepted: 
22.12.2018
Published: 
28.02.2019
Short text (in English):
(downloads: 72)