Predictive Thermal Comfort Control for Cyber-Physical Home Systems

With the emergence of Internet of Things (IoT) and smart homes, the demand for energy efficient thermal comfort has also increased significantly to address the importance of quality of life (QoL) in a modern society. In this paper, we present a model predictive control (MPC) based thermal comfort controller for cyber-physical home systems (CPHS). The MPC controller is integrated into the existing Energy Efficient Thermal Comfort Control (EETCC) system that was developed for the experimental smart house, iHouse. The advantages of MPC was explored in a real time manner for reference tracking and energy minimization scenarios. Besides, Predicted Mean Vote (PMV) index is also adopted into the MPC controller to further enhance the energy efficiency and thermal comfort of the CPHS. The proposed methods are evaluated and verified under various seasons in a CPHS simulation using raw environmental data from the iHouse.