@inproceedings{90ba15a003c742229bfb94284992ee90,
title = "A Review On Data Driven Control Techniques Within Industrial Heating Furnaces",
abstract = "This study presents a comprehensive review of recent advancements in data-driven control techniques applied to industrial heating furnaces. The investigation focuses on three prominent approaches: fuzzy-PID controllers, neural network controllers utilizing model reference control, and Genetic Algorithm (GA) techniques for PID parameter optimization. These data-driven methodologies demonstrated good performance metrics compared to conventional control strategies based on their results. This paper contributes to the field by synthesizing current knowledge, identifying research gaps, and proposing future directions that could lead to more efficient, robust, and widely applicable control solutions for diverse heating furnace systems in the heating industry.",
keywords = "Data driven control, Fuzzy logic, Genetic Algorithm, industrial furnance, Neural network",
author = "Donkor, \{David N.\} and Ogudo, \{Kingsley A.\} and Vikash Rameshar",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 33rd Southern African Universities Power Engineering Conference, SAUPEC 2025 ; Conference date: 29-01-2025 Through 30-01-2025",
year = "2025",
doi = "10.1109/SAUPEC65723.2025.10944369",
language = "English",
series = "Proceedings of the 33rd Southern African Universities Power Engineering Conference, SAUPEC 2025",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings of the 33rd Southern African Universities Power Engineering Conference, SAUPEC 2025",
address = "United States",
}