Physics-constrained deep learning of multi-zone building thermal dynamics
We present a physics-constrained deep learning method to develop control-oriented models
of building thermal dynamics. The proposed method uses systematic encoding of physics …
of building thermal dynamics. The proposed method uses systematic encoding of physics …
Building modeling as a crucial part for building predictive control
Recent results show that a predictive building automation can be used to operate buildings
in an energy and cost effective manner with only a small retrofitting requirements. In this …
in an energy and cost effective manner with only a small retrofitting requirements. In this …
Model predictive control for HVAC systems—A review
The world faces an energy problem. Oil supply is gradually running out. Its use is polluting
the planet with greenhouse gas. Most alternative energy sources also pose some …
the planet with greenhouse gas. Most alternative energy sources also pose some …
Control-oriented thermal modeling of multizone buildings: Methods and issues: Intelligent control of a building system
The residential and commercial building sector is known to use around 40% of the total end-
use energy and, hence, is considered to be the largest energy consumer sector in the world …
use energy and, hence, is considered to be the largest energy consumer sector in the world …
Towards the real-life implementation of MPC for an office building: Identification issues
Modern control methods such as Model Predictive Control (MPC) are getting popular in
recent years in many fields of industry. One of the branches that have witnessed great …
recent years in many fields of industry. One of the branches that have witnessed great …
Process analytical chemistry
J Workman Jr, B Lavine, R Chrisman… - Analytical chemistry, 2011 - ACS Publications
REVIEW an earlier paper of special significance is referenced. The key aspects of this
review include advances in measurement technologies that are applicable for at-line or …
review include advances in measurement technologies that are applicable for at-line or …
A data-driven predictive controller design based on reduced Hankel matrix
H Yang, S Li - 2015 10th Asian Control Conference (ASCC), 2015 - ieeexplore.ieee.org
A data-driven predictive control methodology based on reduced Hankel matrix is proposed
in this paper. Undersome assumptions, the properties of a system can be simply and visually …
in this paper. Undersome assumptions, the properties of a system can be simply and visually …
Model-based energy efficient control applied to an office building
According to numerous studies, up to 40% of the total energy is consumed in the building
sector. Energy reduction in this sector by means of cost-effective and scalable approaches …
sector. Energy reduction in this sector by means of cost-effective and scalable approaches …
Set membership identification of linear systems with guaranteed simulation accuracy
M Lauricella, L Fagiano - IEEE Transactions on Automatic …, 2020 - ieeexplore.ieee.org
In this article, the problem of model identification for linear systems is considered, using a
finite set of sampled data affected by a bounded measurement noise, with unknown bound …
finite set of sampled data affected by a bounded measurement noise, with unknown bound …
MPC relevant identification method for Hammerstein and Wiener models
R Quachio, C Garcia - Journal of Process Control, 2019 - Elsevier
This work focuses on obtaining models that may produce a better performance of Model
Predictive Controllers-MPC. Several papers published in the last 25 years have proposed …
Predictive Controllers-MPC. Several papers published in the last 25 years have proposed …