Mechatronic Module with Alternative-Probability Control

Authors

DOI:

https://doi.org/10.20535/2521-1943.2025.9.4(107).345026

Keywords:

mechatronic module, automation, alternative probabilistic control, adaptive algorithms, system operating modes

Abstract

This article presents control algorithms for adaptive mechanical systems. Object of research: processes occurring in industrial hydraulic drive systems during their operation. Subject of research: dependence of operational efficiency of industrial hydraulic drive systems on the term and operating modes, and applied fundamental circuit solutions and technical means that affect the functional, energy, and cost indicators of the system.The problems solved in the presented article are actual tasks. They involve the use of previous experience in the operation of a specific mechatronic system in specific conditions, for the formation of an adaptive control algorithm. The study is based on the creation of logical interpretations in the algorithm for decision-making. The simultaneous consideration of logical connections and the probability of the component “success of system actions” is considered. On the basis of which a two-component structure of logical expressions of control commands is formed. Accordingly, examples are given for evaluating each of the operation options. The article presents the scope and conditions of practical use of the obtained results. They are based on several examples, namely, the technical implementation of the manipulator macromodule with alternative probabilistic control is considered. It is possible to use the success of the system’s actions and the choice of the option for distributing attempts by digits or/and the basis of logarithmic weight. The peculiarity of the obtained results lies in the use of the criterion of “volume of involved memory” in the control system. This makes it possible to prioritize one of the alternative reactions of the system to external excitation, which provides a basis for the formation of control commands.

References

  1. A. Rojko, “Industry 4.0 Concept: Background and Overview”, iJIM, Vol. 11, No. 5, pp. 77–90, 2017, doi: https://doi.org/10.3991/ijim.v11i5.7072.
  2. L. Kozlov and Y. Burennikov, “Mechatronic Hydraulic System with Adaptive Controller on the Basis of Neural Networks,” Uni- versitatea Tehnica “Gheorghe Asachi” din Iasi Tomul LXI (LXV), Fasc. 1–2, pp. 151–159, 2015. https://sim.tuiasi.ro/wp-con- tent/uploads/2015/03/Stiinta-si-Ingineria-Materialelor-1-2-pe-2015.pdf.
  3. J. Lee, H.-A. Kao and S. Yang, “Service innovation and smart analytics for Industry 4.0 and big data environment, Procedia CIRP, Vol. 16, pp. 3–8, 2014, doi: https://doi.org/10.1016/j.procir.2014.02.001.
  4. Li, Y., H. Wang and J. Zhang, “Precise control of hydraulic actuators using adaptive backstepping and neural networks”, Computers, Materials & Continua, 141(2), pp. 1235–1250, 2024, doi: https://doi.org/10.32604/cmc.2024.041234.
  5. Lucia Knapčíková, Industry 4.0: Trends in Management of Intellegent Manufacturing Systems, Springer, 146 p. ISBN 3030140113, 9783030140113, 2019, doi: https://doi.org/10.1007/978-3-030-14011-3.
  6. M. Brettel, N. Friederichsen, M. Keller and M. Rosenberg, “How Virtualization, Decentralization and Network Building Change the Manufacturing Landscape: An Industry 4.0 Perspective”, International Journal of Mechanical, Aerospace, Industri-al, Mech- atronic and Manufacturing Engineering, Vol. 8, No. 1, рр. 37–44, 2014.
  7. L. Schmidt and K. Hansen, “Electro-Hydraulic Variable-Speed Drive Networks–Idea, Perspectives, and Energy Saving Po-ten- tials”, Energies, Vol. 15(3), 1228, 2022, doi: https://doi.org/10.3390/en15031228.
  8. T. Bauernhansl, M. ten Hompel and B. Vogel-Heuser, Industrie 4.0 in Produktion, Automatisierung und Logistik: Anwen-dung Technologien Migration, Springer-Verlag, 2014, doi: https://doi.org/10.1007/978-3-658-04682-8.
  9. S.-C. Vanegas-Ayala, J. Baro´n-Velandia and D.-D. Leal-Lara, “A systematic review of greenhouse humidity prediction and control models using fuzzy inference systems,” Advances in Human-Computer Interaction, 2022, doi: https://doi.org/10.1155/2022/8483003.
  10. S. Zhao et al., “A High-Order Load Model and the Control Algorithm for an Aerospace Electro-Hydraulic Actuator”, Actua-tors, Vol. 10(3), p. 53, 2021, doi: https://doi.org/10.3390/act10030053.
  11. P. K. Anokhyn, Byolohyia y neirofyzyolohyia uslovnoho refleksa, Moscow: Medytsyna, 1968.
  12. K. O. Belikov and O. P. Gubarev, “Adaptation of control in electropneumatic systems with discrete software control”, Bulletin of the National Technical University “KhPI”, Series: Hydraulic machines and hydraulic units, No. 1, pp. 18–22, 2020.
  13. O. S. Hanpantsurova and O. P. Gubarev, “Lohiko-inertsiina skladova komand keruvannia vykonavchym modulem mek-hatronnoi systemy,” in Proc. XVII MNTK AS PHP “Promyslova hidravlika i pnevmatyka”, Kharkiv, 2016.
  14. M. V. Hlushkov, Yu. V. Kapytonova and A. T. Myshchenko, Lohichne proektyvannya dyskretnukh prystroiv, Kyiv: Naukova dumka, 1987.
  15. A.P. Gubarev, Dyskretno-lohychne upravlinnya v systemakh hydropnevmoavtomatyky, Kyiv: YSMO, 1997, ISBN 5-7763-8725-6.
  16. A. P. Gubarev, Do putannya adaptacyy lohychnoho keruvannya, Deponent: UkrNYYNTY, N282-Uk86, 1986.
  17. L. H. Kozlov, “Using neural network for regulation time reduction in the mechatronic hydraulic system,” Visnyk Sumskoho derzhavnoho universytetu. Seriia “Tekhnichni nauky, No. 4, pp. 165–174, 2013, https://essuir.sumdu.edu.ua/handle/123456789/33794.
  18. T. Petrakis et al., “Neural Network Model for Greenhouse Microclimate Predictions”, Agriculture, Vol. 12(6), 2022, doi: https://doi.org/10.3390/agriculture12060780.
  19. V. P. Tarasyk and S. A. Runkevych, Intellektualny systemy upravlinnya avtotransportnymy zasobamy: Monohrafyia, Mn.:UP “Tekhnoprynt”, 2004, 512 p. ISBN 985-464-664-5.
  20. M. V. Cherkashenko, Avtomatyzatsiya proektuvannya system hidro- i pnevmopryvodiv z dyskretnym upravlinnyam, Kharkiv: NTU “KhPY”, 2007, 210 p. ISBN 5-217-01882-8.

Downloads

Published

2025-12-29

How to Cite

[1]
O. Gubarev, K. Belikov, and A. Murashchenko, “Mechatronic Module with Alternative-Probability Control”, Mech. Adv. Technol., vol. 9, no. 4(107), pp. 432–441, Dec. 2025.

Issue

Vol. 9 No. 4(107) (2025)

Section

Mechanics

License

Copyright (c) 2025 Альона Муращенко, Олександр Губарев, Костянтин Бєліков

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The ownership of copyright remains with the Authors.
 
Authors may use their own material in other publications provided that the Journal is acknowledged as the original place of publication and National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” as the Publisher.

Authors who publish with this journal agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under CC BY 4.0 that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.

  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work