ABSTRACT
Steam boilers and steam generators represent essential equipment for energy conversion in industrial plants, primarily aimed at producing steam and subsequently generating electricity. Processes in thermal power systems are characterized by a high degree of complexity and nonlinearity, which necessitates the application of modern automatic control theories based on accurate mathematical models in state space. Given the dynamic behavior and interdependence of process variables, the implementation of control algorithms is not feasible without the use of computer technology and advanced measurement systems, which are essential for real-time process identification. Effective application of this approach requires knowledge of both the static and dynamic characteristics of the processes occurring within a thermal power plant. Mathematical modeling is based on the formulation of balance and supplementary equations, which together form a closed system for solving. A certain set of parameters is adopted in advance, while others require estimation due to the inability to determine them precisely, which may lead to some deviations in model accuracy. If such deviations are not significant, they can be corrected through the application of process identification methods, i.e., by estimating the insufficiently known parameters. This paper focuses on the identification of the dynamic behavior of the process, with the aim of developing more reliable mathematical models as a foundation for designing advanced control systems.
KEYWORDS
PAPER SUBMITTED: 2025-08-01
PAPER REVISED: 2025-09-17
PAPER ACCEPTED: 2025-09-29
PUBLISHED ONLINE: 2025-11-08
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