This study is devoted to improving the economic efficiency of the cell, due to the field of the generated electromagnetic field’s accurate diagnostics. To solve this problem, the authors had developed a hardware-software complex for electromagnetic field diagnostics. This complex includes a measurement device and a software package for data collection and analysis. On the laboratory prototype of the aluminum electrolysis complex, a study was carried out on the formation and structure of the electromagnetic field. A number of experiments have been carried out showing the degree of formation of the electromagnetic field by the anode, the relationship of electromagnetic fields in the inter-anode space has been shown. Based on the results of the studies, conclusions were drawn about the possibility of diagnosing the current state of the anode, determining the direction of rotation of aluminum in the electrolytic cell and estimating the life of the anode and its burnout time.

Oil is one of the main resources used by all countries in the world. The ever-growing demand for oil and oil products forces oil companies to increase production and refining. In order to increase net profit, oil producing companies are constantly upgrading equipment, improving oil production technologies, and preparing oil for further processing. When considering the elements of primary oil refining in difficult conditions, such as hard-to-reach or in remote locations, developers face strict limitations in energy resources and dimensions. Therefore, the use of traditional systems causes a number of difficulties, significantly reducing production efficiency. In this study, the authors solve the problem of improving the characteristics of the oil separation process. In their work, the authors analyzed the separation columns of primary oil distillation, identified the shortcomings of the technological process, and searched for technological solutions. Having identified the lack of technical solutions for monitoring the state of the temperature field of the separation column, the authors developed their own hardware–software complex for monitoring the separation column (RF patents No. 2020665473, No. 2021662752 were received). The complex was tested and successfully implemented into production. The study provides an assessment of the economic efficiency of implementation for a year and a forecast of the economic effect for 10 years.

Natural gas separation and purification are critical stages for ensuring product quality, operational safety, and economic efficiency in the energy sector. However, a significant research gap exists: conventional control systems, predominantly based on a proportional-integral-derivative (PID) controller, are often static and lack the adaptability required to handle fluctuations in raw gas composition and operating conditions. This review aims to systematically analyze modern control strategies to identify the most influential parameters and effective methodologies for enhancing process efficiency. The methods involve a comparative assessment of classical PID control against advanced intelligent approaches, including adaptive control, fuzzy logic, and machine learning (ML) models, based on a synthesis of the recent literature and industrial case studies. The key finding is that data-driven and intelligent methods (e.g., neural networks, adaptive fuzzy controllers) demonstrate superior performance in achieving precise parameter adjustment, improving responsiveness, and optimizing energy consumption compared to traditional static systems. Such an integrated strategy transforms decision-making into a multivariable optimization framework with objectives encompassing minimizing pollutants, lowering energy usage, and enhancing end-product specifications. The present work argues for employing methodologies like systemic analyses and advanced computational techniques—particularly artificial neural networks—to forecast gas stream attributes.

Modern oil refining is faced with the need to maximize raw material processing in the face of fierce competition and environmental requirements. Therefore, the fluid catalytic cracking (FCC) process, key to the production of high-octane gasoline, requires special attention to automation efficiency. Maintaining optimal reactor temperature is a complex scientific and technical challenge, the solution to which directly impacts the yield of target products and the service life of the catalyst. Existing automatic control systems often fail to cope with process transients, nonlinearities, and time delays, making the search for new control approaches highly relevant. The scientific significance of this study lies in the system analysis and quantitative comparison of the effectiveness of classical control laws (P, PI, PID) applied to a plant with a delay. For the first time, a rigorous comparative analysis of tuning methods—analytical (based on phase margin specifications) and automated (using the PID Tuner tool in MATLAB Simulink R2024b)—is performed for a plant characterized as a second-order system with time delay, formed by the series connection of two first-order lag elements with transport delay. The results contribute to automatic control theory by clearly demonstrating the limitations of the proportional controller and the insufficient speed of the integral controller, as well as confirming the hypothesis that a PID law is necessary to achieve a balance between accuracy and response speed under inertia conditions. The practical significance of the work is confirmed by the development of an optimized automatic temperature control system. Using the PID Tuner tool, we achieved critical industrial performance indicators: zero static error, minimal control time (44 s), and acceptable overshoot (9.6%). The system’s robustness (maintaining stability with changes in plant parameters by 30–40%) and its invariance to the main disturbance (catalyst temperature fluctuations), confirmed during simulation, guarantee the viability of the proposed solution under real-world production conditions. Implementation of such a controller will minimize deviations from the process conditions, leading to increased yield of light petroleum products and an extended service life of the expensive catalyst, providing direct economic benefits.