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 last few years, the application of Model Predictive Control (MPC) for energy
management in buildings has received significant attention from the research community …

Buildings consume about 40% of globally-produced energy. A notable amount of this energy
is used to provide sufficient comfort levels to the building occupants. Moreover, given recent …

This work presents a literature review of control methods, with an emphasis on the theory
and applications of model predictive control (MPC) for heating, ventilation, and air …

Buildings are responsible for about 30–40% of global energy demand. At the same time, we
humans spend almost our entire life, up to 80–90% of the time, inside of buildings. Reducing …

Energy optimization in buildings by controlling the Heating Ventilation and Air Conditioning
(HVAC) system is being researched extensively. In this paper, a model-free actor-critic …

This paper presents an application case study of an economic model predictive control
(EMPC) method for optimizing the building demand and energy cost under the time-of-use …

Artificial intelligence (AI) controls are commonly used to save energy. However, excessive
diversity in technological development has resulted in the inability to provide consistent …

Over the past several years, studies have been conducted on the model predictive control
(MPC), which has analyzed the amount of savings through model-based predictive control …

The objective of this study is to demonstrate the effectiveness of model predictive control
(MPC) in reducing the energy and demand costs for buildings in an electricity grid with time …