Heat exchangers are critical components in industrial processes, requiring precise temperature control to ensure efficiency, safety, and energy conservation. Traditional Proportional-IntegralDerivative (PID) controllers have been widely used, but they often struggle with nonlinearities, disturbances, and parameter variations inherent in heat exchanger systems. Fuzzy logic controllers (FLCs) and hybrid fuzzy PID approaches have emerged as robust alternatives, offering adaptive tuning and improved performance. This review synthesizes key literature from the past three decades, drawing from foundational works on conventional PID tuning, fuzzy logic integration, and optimization techniques such as genetic algorithms. Additionally, recent advancements are examined, highlighting innovations in metaheuristic optimization and fractional-order fuzzy PID designs. Theanalysis reveals trends toward hybrid intelligent systems for enhanced stability and energy efficiency, while identifying challenges like computational complexity and real-time implementation. Future directions include AI-driven self-tuning and integration with Industry 4.0 technologies
Patidar et al. (Thu,) studied this question.
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