Building systems are subject of dynamic system that have a general feature of non-linearity
and in turn, present us with different challenges for its optimized control of energy-saving …

In the past ten years many Stochastic Model Predictive Control (SMPC) algorithms have
been developed for systems subject to stochastic disturbances and model uncertainties …

This paper focuses on the control of microgrids where both gas and electricity are provided
to the final customer, ie, multi-carrier microgrids. Hence, these microgrids include thermal …

Improving the energy efficiency of Heating, Ventilation, and Air Conditioning (HVAC)
systems is crucial to reduce buildings' energy costs and their carbon footprint. HVAC …

This research applies a data-driven approach to investigate energy savings of a multi-zone
HVAC (heating, ventilating, and air conditioning) system. The predictive models of the HVAC …

This article studies a scalable control method for multizone heating, ventilation, and air-
conditioning (HVAC) systems to optimize the energy cost for maintaining thermal comfort …

We address the problem of estimating the occupancy levels in rooms using the information
available in standard HVAC systems. Instead of employing dedicated devices, we exploit the …

State-of-the-art Model Predictive Control (MPC) applications for building heating adopt
either a deterministic controller together with a nonlinear model or a linearized model with a …

Owing to the call for energy efficiency, the need to optimize the energy consumption of
commercial buildings-responsible for over 40% of US energy consumption-has recently …

Buildings are responsible for a significant portion of energy consumption in the US,
accounting for more than 40% of US primary energy consumption. Heating, ventilation and …