| Issue |
E3S Web Conf.
Volume 689, 2026
14th International Symposium on Heating, Ventilation, and Air Conditioning (ISHVAC 2025)
|
|
|---|---|---|
| Article Number | 03003 | |
| Number of page(s) | 6 | |
| Section | Heating / Cooling Performance and Optimization | |
| DOI | https://doi.org/10.1051/e3sconf/202668903003 | |
| Published online | 21 January 2026 | |
Comparative study of different control strategies for radiant ceiling panel system
Department of Architecture, Tokyo Denki University, Tokyo 120-8551, Japan
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
Radiant ceiling panel (RCP) system has been increasingly adopted in recent years. However, its optimal control strategies have yet to be established. In previous studies, a grey-box model has been developed to predict the indoor thermal condition when using a RCP system. Based on this model, a control framework was implemented in MATLAB/Simulink, in which the inlet water temperature was regulated by a controller to maintain the indoor air temperature at a setpoint of 20 ℃. Different sampling period (1 min,10 min, 30 min and 1hour) were investigated with respect to system accuracy. Three control strategies- on off control, PID control, and model predictive control (MPC) were evaluated in terms of their performance on indoor temperature control and energy consumption reduction. For PID control, the gains were tuned by Ziegler–Nichols tuning method, and performance comparisons were made among P control, PI control and PID control. The results show that both PID control and MPC can effectively maintain the indoor temperature at the setpoint while consuming less energy consumption compared to on off control. In particular, MPC outperformed PID control by exhibiting fewer temperature fluctuations, owing to its ability to optimize control actions based on future state predictions.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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