Robust Control of Heat Diffusion Systems with Time Delay Using Fuzzy Logic and Model-Based Compensation

Traditional heat diffusion systems are typically regulated using Proportional–Integral–Derivative (PID) controllers. PID controllers still remain the backbone of numerous industrial control applications due to their simplicity, robustness, and efficiency. However, traditional tuning methods—such as Ziegler–Nichols or Cohen–Coon—often exhibit limitations when applied to systems with nonlinear dynamics, time-varying behaviors, or parametric uncertainties. To address these challenges, Fuzzy Logic Controllers (FLC) have emerged as a promising hybrid strategy, by translating quantitative and imprecise linguistic inputs into quantitative control actions, thereby enabling more adaptive and precise regulation. This is achieved through the integration of fuzzy inference mechanisms that dynamically adjust PID gains in response to changing system conditions. This study proposes a fuzzy logic control strategy for a heat diffusion system and conducts a comparative analysis against conventional PID control. The methodology encompasses system modeling, design of the fuzzy inference system, and simulation studies. To improve transient response and address time delays, additional features such as Anti-Windup compensation and a Smith Predictor are integrated into the control scheme. The final validation step involves the introduction of simulated environmental disturbances, including abrupt temperature drops, to evaluate the controller’s robustness. Simulation results demonstrate that the proposed FLC provides superior dynamic performance compared to the conventional PID controller, achieving approximately 5–7% faster rise time and 8–10% lower settling time. The incorporation of an anti-windup mechanism did not yield significant benefits in this application. In contrast, the integration of a Smith Predictor further reduced oscillatory behavior and substantially improved disturbance rejection, tracking accuracy, and adaptability under simulated thermal variations. These results underscore the effectiveness of the FLC in handling systems with time delays and nonlinearities, reinforcing its role as a robust and adaptable control strategy for thermal processes with complex dynamics.