INTEGRATED ARTIFICIAL INTELLIGENCE-BASED CONTROL SYSTEM FOR OPTIMIZING TEMPERATURE, PRESSURE, AND COMBUSTION PROCESSES IN GAS-FIRED INDUSTRIAL FURNACES
DOI:
https://doi.org/10.47390/ts-v3i12y2025N06Keywords:
gas-fired furnace, artificial intelligence, fuzzy logic, neural network, integrated control, energy efficiency, combustion process, temperature control.Abstract
This paper addresses the development of an integrated intelligent control system based on artificial intelligence for optimizing temperature, pressure, and combustion processes in gas-fired industrial furnaces. The main objective of the study is to improve the efficiency of thermal and energy processes in furnaces, ensure complete fuel combustion, and reduce overall energy consumption. Conventional PID controllers fail to provide sufficient accuracy under conditions of dynamic uncertainties, external disturbances, and abrupt changes in technological parameters. Therefore, this work proposes the design of an adaptive control structure based on neural networks, fuzzy logic, and hybrid intelligent algorithms. The developed system enables real-time monitoring of temperature, pressure, and gas–air ratio, optimizes the combustion process through predictive analysis, and prevents emergency operating conditions. Control algorithms were modeled in the MATLAB/Simulink environment, and a comparative analysis with a classical PID control system was conducted. The results demonstrate that the artificial intelligence-based integrated control system improves temperature stability by 18–25% and increases energy efficiency by 12–20%. The obtained scientific results can be widely applied in metallurgical, glass-melting, ceramic, and construction materials industries.
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