Abstract
The feasibility of real-time control of complex motion is considered, with variation in the length of the control cycle, the velocity of the object, and the response time of the system. The condition governing the feasibility is derived.
REFERENCES
Gribkov, A.A., Pivkin, P.M., and Zelenskii, A.A., State industrial policy and the machine-tool industry, Russ. Eng. Res., 2021, vol. 41, pp. 342–346. https://doi.org/10.3103/S1068798X21040092
Zelenskii, A.A., Morozkin, M.S., Panfilov, A.N., et al., Russian high-precision technological equipment import analysis, Izv. Tul’sk. Gos. Univ. Tekh. Nauki, 2021, no. 9, pp. 203–207.
Belov, V.B., New paradigm of industrial development of Germany—strategy “Industry 4.0,” Sovr. Evropa, 2016, no. 5, pp. 11–21.
Fuchs, C., Industry 4.0: the digital German ideology, TripleC: Commun., Capitalism, Critique, 2018, vol. 16, no. 1, pp. 280–289.
Suh, S.-H., Kang, S.-K., Chung, D.-H., et al., Theory and Design of CNC Systems, London: Springer, 2008.
In-Process Correction Technology Added for Hybrid Metal 3D Printer, 2017 Amazing. https://additivemanufacturing.com/2017/07/11/sodick-announces-new-in-process-correction-technology-for-hybrid-metal-3d-printer/.
Kozak, J. and Zakrzewski, T., Accuracy problems of additive manufacturing using SLS/SLM processes, AIP Conf. Proc., 2017, vol. 2017, no. 1, p. 020010. https://doi.org/10.1063/1.5056273
Gokuldoss, P., Kolla, S., and Eckert, J., Additive manufacturing processes: selective laser melting, electron beam melting and binder jetting—selection guidelines, Materials, 2017, vol. 10, no. 6, p. 672. https://doi.org/10.3390/ma10060672
Gruber, S., Grunert, C., Riede, V., et al., Comparison of dimensional accuracy and tolerances of powder bed based and nozzle based additive manufacturing processes, J. Laser Appl., 2020, vol. 32, p. 032016.
3D Metal Printer SLM Solutions NXG XII 600, Globatek JSC, 2008–2021. https://3d.globatek.ru/production/slm_nxg_xii_600/.
Turomsha, V.I., High-speed power milling, Vestn. Polotsk. Gos. Univ., Ser. C, 2012, no. 3, pp. 56–64.
Korop, A.D., Improving the efficiency of manufacturing titanium alloy parts, Extended Abstract of Cand. Sci. (Eng.) Dissertation, Belgorod: Belgorod. Gos. Tekhnol. Univ. im. V.G. Shukhova, 2011.
Zakhama, A., Charrabi, L., and Jelassi, K., Intelligent Selective Compliance Articulated Robot Arm robot with object recognition in a multi-agent manufacturing system, Int. J. Adv. Rob. Syst., 2019, pp. 1–15. https://doi.org/10.1177/1729881419841145
Kuznetsov, A., The main objectives of formation in independent of imports machine tool industry in Russia, Stankoinstrument, 2016, no. 2, pp. 16–25.
Poduraev, V.N., Avtomaticheski reguliruemye i kombiniruemye protsessy rezaniya (Automatically Adjustable and Combinable Cutting Processes), Moscow: Mashinostroenie, 1977.
Kuznetsov, A., Directions of development of metal cutting machine: system principles. Part 1, Stankoinstrument, 2020, no. 3, pp. 30–41.
Kuznetsov, A., Directions of development of metal-cutting machines: system principles. Part 2, Stankoinstrument, 2020, no. 4, pp. 36–45.
Kuznetsov, A.P., Trends in development and efficient production of machines. Part 1. Physical basis of production systems development, Stankoinstrument, 2021, no. 2, pp. 40–48.
Ayupov, V.V., Matematicheskoe modelirovanie tekhnicheskikh sistem: Uchebnoe posobie (Mathematical Modeling of Technical Systems: Manual), Perm’: Prokrost’, 2017.
Tyutikov, V.V., Analysis of complexity factors in the synthesis of modal control systems, Izv. Taganrog. Radiotekh. Univ., 2005, no. 1, pp. 44–46.
Krotov, V.F. et al., Osnovy teorii optimal’nogo upravleniya (Fundamentals of Optimal Control Theory), Moscow: Vysshaya Shkola, 1990.
Il’yasov, B.G., Makarova, E.A., Zakieva, E.Sh., et al., Methodological foundations of modeling and intelligent management of an industrial complex as a complex dynamic multiagent object, Sovr. Naukoem. Tekhnol., 2020, no. 11-2, pp. 288–293.
Knyazeva, E., Strategies of dynamic complexity management, Forsait, 2020, vol. 14, no. 4, pp. 34–45.
Gaides, M.A., Obshchaya teoriya sistem (sistemy i sistemnyi analiz) (General Theory of Systems (Systems and System Analysis)), Vinnitsa: Globus-Press, 2005.
Zakharchuk, O.G., Application complexity assessment for optimization of management subsystems, Strateg. Biznes., 2014, no. 2 (4), pp. 29–38.
Labinskii, A.Yu. and Afonin, P.N., The problem of use the neural networks for the automatic control system, Vestn. S.-Peterb. Univ. Gos. Protivopozhar. Sluzhby MChS Rossii, 2017, no. 2, pp. 100–106.
Blagin, A.V., Blagina, L.V., Popova, I.G., et al., Entropy analysis of complex systems as a tool of engineering activity, Inzh. Vestn. Dona, 2018, no. 4 (51), pp. 288–293.
Pugachev, V.S., Teoriya sluchainykh funktsii i ee primenenie k zadacham avtomaticheskogo upravleniya (Theory of Random Functions and Its Application to Automatic Control Problems), Moscow: Fizmatlit, 1960.
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Financial support was provided by the Russian Ministry of Education and Science within the framework of a grant for fundamental research by educational establishments between 2022 and 2022 (project FSFS-2021-0004).
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Zelenskiy, A.A., Kuznetsov, A.P., Ilyukhin, Y.V. et al. Feasibility of Controlling the Motion of Industrial Robots, CNC Machine Tools, and Mechatronic Systems. Part 1. Russ. Engin. Res. 43, 27–34 (2023). https://doi.org/10.3103/S1068798X23020260
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DOI: https://doi.org/10.3103/S1068798X23020260