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Physics-informed hierarchical data-driven predictive control for building HVAC systems to achieve energy and health nexus
Xuezheng Wang,
Bing Dong
Department of Mechanical & Aerospace Engineering
Research output
:
Contribution to journal
›
Article
›
peer-review
15
Scopus citations
Overview
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Dive into the research topics of 'Physics-informed hierarchical data-driven predictive control for building HVAC systems to achieve energy and health nexus'. Together they form a unique fingerprint.
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Engineering
Energy Engineering
100%
Predictive Control
100%
Control Strategy
87%
Air Quality
25%
Energy Conservation
12%
Indoor Air
12%
Dynamic Models
12%
Control Input
12%
Primary Energy
12%
Temperature Profile
12%
Thermal Comfort
12%
Predictive Control Model
12%
Cooling Load
12%
Space Cooling
12%
Keyphrases
Data-driven Predictive Control
100%
Physics-informed
100%
Input Convex Neural Networks
50%
Air Side
33%
Weather Forecasting Model
16%
Indoor Temperature Profile
16%
Bad Controls
16%
Space Cooling Load
16%
Consistent Behavior
16%
Primary Energy Use
16%
Sanity Checks
16%
Chemical Engineering
Neural Network
100%
Predictive Control Model
33%
Material Science
Predictive Control Model
100%