PID Controller Tuning for Heat Exchanger Systems: A Comparative Study of Classical, Model-Based, Optimization, and Reinforcement Learning Approaches

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Key Points

This study aims to compare different PID controller tuning methods for heat exchangers to determine the most effective approach for temperature control.
Comparative analysis of PID tuning methods: Ziegler–Nichols, Internal Model Control, Particle Swarm Optimization, Soft Actor-Critic.
Single run executed for ZN and IMC using fixed hyperparameters.
Two-stage methodology for PSO and SAC with hyperparameter selection via random search.
Statistical analysis conducted on performance metrics: RMSE, IAE, ISE, ITAE.
PSO-PID achieves the lowest error metrics for all reference signals.
In the step response, PSO provides 90.8% improvement in ITAE and 25.2% improvement in RMSE compared to ZN.
Statistical analysis shows significant differences between PSO and SAC for most metrics.

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Comparative analysis of PID tuning methods improves temperature control in industrial heat exchangers, indicating effective strategies.

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Sertaç Savaş (2026) studied this question.

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