Energy-Aware Thermal Regulation for Sustainable Industrial Systems Under Dew-Point Constraints: A Comparative Experimental Study of Control Strategies

Energy-efficient operation of industrial thermal systems is a key requirement for sustainable manufacturing and resource-aware process design, particularly under environmental constraints such as dew-point conditions. In this context, minimizing energy consumption while maintaining stable thermal regulation is essential to reduce operational costs and improve system sustainability. This work presents an energy-aware experimental comparison of three control strategies—classical PID, fractional-order PID (FOPID), and hysteresis control—applied to a real thermoelectric thermal regulation system operating under dynamic ambient conditions and dew-point constraints. Unlike conventional control studies focused primarily on tracking performance, this research adopts a sustainability-oriented multi-criteria evaluation framework that explicitly positions energy consumption as a first-order assessment dimension alongside thermal regulation quality and control effort. A set of physically consistent performance indicators is introduced, including total energy consumption, control effort, energy-per-regulation metrics, and a global energy efficiency index, enabling a comprehensive assessment of industrial thermal control strategies from a resource efficiency perspective. Experimental results demonstrate that controller evaluation strongly depends on the inclusion of energy-based metrics. While PID control achieves competitive tracking performance with low error, FOPID provides the best overall trade-off between thermal accuracy and energy consumption, resulting in the highest energy efficiency index. In contrast, hysteresis control, despite its structural simplicity and robustness, leads to higher energy usage due to frequent switching dynamics, reducing its suitability for energy-constrained sustainable applications. The results highlight that thermal regulation near dew-point constraints should be evaluated through an energy-aware multi-criteria framework rather than through pure tracking metrics, enabling a more complete characterization of controller performance for sustainable industrial applications. The proposed framework provides a scalable methodology for evaluating and designing energy-efficient control strategies, supporting sustainable industrial operation and contributing to resource optimization principles aligned with circular economy objectives.