International Research Journal of Education and Technology

This paper presents a comprehensive investigation into intelligent control strategies for temperature regulation in shell and tube heat exchangers. The research addresses the limitations of conventional PID controllers by implementing advanced computational intelligence techniques including Fuzzy Logic Control (FLC), Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and hybrid evolutionary algorithms. Through extensive simulations in MATLAB/Simulink, the study demonstrates significant improvements in dynamic response characteristics, with the proposed intelligent controllers achieving reduced settling times, minimized overshoots, and enhanced disturbance rejection capabilities. The fuzzy logic controller reduced peak overshoot to 9.469% compared to 74.5% with conventional PID, while settling time decreased from 178 seconds to 5.146 seconds. Performance indices including IAE, ISE, ITAE, and ITSE showed marked improvements across all intelligent control implementations, validating their superiority for industrial heat exchanger applications.