A constrained model predictive control for the building thermal management with optimal setting design

Abstract

<span lang="EN-US">Today, the building sector is the most important consumer of energy. The main challenge in building management is to obtain the desired performance taking into account many aspects such as comfort requirements, variation of building physical characteristics, system constraints, and energy management. For this purpose, a predictive control approach applied to the building thermal has been designed to achieve desired performances combined with an energy optimization approach based on intrinsic system parameters. The developed approach is applied with an online identification system for effective predictive control to take into account the reel building characteristics and to choose the optimal tuning parameters. The simulation results show good performances in terms of accuracy and robustness face to internal and external disturbances with respect to system constraints.</span>

Optimal Neural Network PID Approach for Building Thermal Management

“…Different mathematical models, both extremely simple and complicated, are employed in simulations of the building's energy performance to characterize the heat transfer and capacity in transient and permanent situations. For the implementation, validation, and simulation of the regulation and robustness system, which are important steps in the study, we designed a state model from building components (walls, ceiling, and floor) that were previously validated [25] and whose methods of identification are described in several scientific journals [26].…”