Development of a hybrid adaptive control system for pyrolysis plants: A comparative study of conventional and intelligent approaches
2025
Rysbek Aitolkyn | Sergazin Gani | Zhetenbayev Nursultan
This study presents a comparative evaluation of control systems for automating the pyrolysis process, including PLC, SCADA, Fuzzy Logic, Artificial Neural Networks (ANN), and a hybrid approach. The analysis focuses on key performance indicators such as reliability, adaptability, integration complexity, and predictive capability. Due to the nonlinear and dynamic nature of pyrolysis, selecting an appropriate control architecture is essential for improving efficiency, product quality, and environmental safety. The findings support the implementation of a hybrid control system that integrates the strengths of conventional and intelligent methods, aligning with Industry 4.0 requirements and providing a foundation for digital transformation in industrial waste recycling.
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