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Mathematical Modelling of Automation Objects Throughparametric Identification and Digital Twins
(ХНУРЕ, 2025) Fesenko, A. O.; Kolupaieva, I. V.; Romashov, Yu. V.
The paper considers mathematical modelling of automation objects using linear differential equations, parametric identification, and digital twins. The dynamics of the object model is described through the relationship between the controlled parameter x(t) and the control parameter u(t). Accurate determination of coefficients based on experimental data allows us to adequately reproduce the dynamics of the system and promptly respond to changing operating conditions. Continuous monitoring, forecasting, and optimization of operating modes is facilitated by the integration of digital twins, which are constantly updated using data from sensors and SCADA systems. For high-tech and critical industries of Industry 4.0, it is very important that the synergy of these approaches increases the efficiency, reliability, and safety of automation object management