The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Theory and applications of HVAC control systems – A review of model predictive control (MPC)
Open accessAbstract
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 conditioning (HVAC) systems. Several control methods used for HVAC control are identified from the literature review, and a brief survey of each method is presented. Next, the performance of MPC is compared with that of other control approaches. Factors affecting MPC performance (including control configuration, process type, model, optimization technique, prediction horizon, control horizon, constraints, and cost function) are elaborated using specific examples from the literature. The gaps in MPC research are identified, and future directions are highlighted.
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Citations
Cites
A review on buildings energy consumption information
Pérez-Lombard, L., Ortiz, J., & Pout, C. (2008) · Energy and Buildings · doi:10.1016/j.enbuild.2007.03.007 · Cited by 6,649 · cited 2×
“The categories of building services and heating, ventilation, and air conditioning (HVAC) systems make up the major sources of energy use in buildings (almost 50% [1,2]).”
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Cited by
All you need to know about model predictive control for buildings
Drgoňa, J., Arroyo, J., Cupeiro Figueroa, I., Blum, D., Arendt, K., Kim, D., Ollé, E. P., Oravec, J., Wetter, M., Vrabie, D. L., et al. (2020) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2020.09.001 · Cited by 1,020
Afram, A., Janabi-Sharifi, F., Fung, A. S., & Raahemifar, K. (2017) · Energy and Buildings · doi:10.1016/j.enbuild.2017.02.012 · Cited by 655
Self-citationSerale, G., Fiorentini, M., Capozzoli, A., Bernardini, D., & Bemporad, A. (2018) · Energies · doi:10.3390/en11030631 · Cited by 637
Ten Questions Concerning Model Predictive Control for Energy Efficient Buildings
Killian, M., & Kozek, M. (2016) · Building and Environment · doi:10.1016/j.buildenv.2016.05.034 · Cited by 463
Yao, Y., & Shekhar, D. K. (2021) · Building and Environment · doi:10.1016/j.buildenv.2021.107952 · Cited by 447
Metadata
- Authors
- Afram, A., & Janabi-Sharifi, F.
- Venue
- Building and Environment
- Publisher
- Elsevier BV
- Published
- 2014-02
- Volume
- 72
- Pages
- 343-355
- ISSN
- 0360-1323 (ISSN-L)
- OpenAlex
- W1973944436
- Cited by
- 1,310
- References
- 1
- FWCI
- 61.79
- Type
- journal article
- Language
- en
- Open access
- green
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
