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 …

It has been proven that advanced building control, like model predictive control (MPC), can
notably reduce the energy use and mitigate greenhouse gas emissions. However, despite …

Abstract Model Predictive Control (MPC) is a promising technique to address growing needs
for heating, ventilation, and air-conditioning (HVAC) systems to operate more efficiently and …

A model predictive control system with adaptive machine-learning-based building models
for building automation and control applications is proposed. The system features an …

Managing supply and demand in the electricity grid is becoming more challenging due to
the increasing penetration of variable renewable energy sources. As significant end-use …

Being a primary contributor to global energy consumption and energy-related carbon
emissions, the building and building construction sectors are a crucial player in the …

This paper reviews applications of multi-objective optimization approaches for design,
control, and the combination of both design and control of a single element or a set of …

With the rapid development of high-performance computing technology, data-driven models,
especially deep learning models, are being used increasingly for solar radiation prediction …

Predictive control offers significant advantages in nonlinear control, high thermal inertia, and
dynamic control. This article uses a Systematic Reviews and Meta-Analyses methodology to …

Because physics-based building models are difficult to obtain as each building is individual,
there is an increasing interest in generating models suitable for building MPC directly from …