@article {Berouine2020,
	title = {Towards a real-time predictive management approach of indoor air quality in energy-efficient buildings},
	journal = {Energies},
	volume = {13},
	number = {12},
	year = {2020},
	note = {cited By 6},
	abstract = {Ventilation, heating and air conditioning systems are the main energy consumers in building sector. Improving the energy consumption of these systems, while satisfying the occupants{\textquoteright} comfort, is the major concern of control and automation designers and researchers. Model predictive control (MPC) methods have been widely studied in order to reduce the energy usage while enhancing the occupants{\textquoteright} comfort. In this paper, a generalized predictive control (GPC) algorithm based on controlled auto-regressive integrated moving average is investigated for standalone ventilation systems{\textquoteright} control. A building{\textquoteright}s ventilation system is first modeled together with the GPC and MPC controllers. Simulations have been conducted for validation purposes and are structured into two main parts. In the first part, we compare the MPC with two traditional controllers, while the second part is dedicated to the comparison of the MPC against the GPC controller. Simulation results show the effectiveness of the GPC in reducing the energy consumption by about 4.34\% while providing significant indoor air quality improvement. {\textcopyright} 2020 by the authors.},
	keywords = {Air conditioning, Air quality, Auto-regressive integrated moving average, Control and automation, Controllers, Energy consumer, energy efficiency, Energy efficient building, Energy utilization, Generalized predictive control, Heating-and-air conditioning system, Indoor air pollution, Indoor air quality, Intelligent buildings, Model predictive control, Predictive control systems, Ventilation, Ventilation systems},
	doi = {10.3390/en13123246},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089987718\&doi=10.3390\%2fen13123246\&partnerID=40\&md5=bdf8cea22143a02d8648fcb8c208a7b9},
	author = {Berouine, A. and Ouladsine, R. and Bakhouya, M. and Essaaidi, M.}
}
@conference {Boulmrharj2018,
	title = {Towards a battery characterization methodology for performance evaluation of micro-grid systems},
	booktitle = {2018 International Conference on Smart Energy Systems and Technologies, SEST 2018 - Proceedings},
	year = {2018},
	doi = {10.1109/SEST.2018.8495829},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056492547\&doi=10.1109\%2fSEST.2018.8495829\&partnerID=40\&md5=f25a82d795aa6991c23f1064013cde45},
	author = {Boulmrharj, S. and NaitMalek, Y. and Mouatamid, A.E. and Ouladsine, R. and Bakhouya, M. and Ouldmoussa, M. and Zine-Dine, K. and Khaidar, M. and Abid, R.}
}
@conference {Elmouatamid2018984,
	title = {Towards a Demand/Response Control Approach for Micro-grid Systems},
	booktitle = {2018 5th International Conference on Control, Decision and Information Technologies, CoDIT 2018},
	year = {2018},
	pages = {984-988},
	doi = {10.1109/CoDIT.2018.8394951},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050227456\&doi=10.1109\%2fCoDIT.2018.8394951\&partnerID=40\&md5=97a6b224a481de8a0d5d91a46b76b895},
	author = {Elmouatamid, A. and NaitMalek, Y. and Ouladsine, R. and Bakhouya, M. and Elkamoun, N. and Zine-Dine, K. and Khaidar, M. and Abid, R.}
}
@conference {Lachhab2018926,
	title = {Towards an Intelligent Approach for Ventilation Systems Control using IoT and Big Data Technologies},
	booktitle = {Procedia Computer Science},
	volume = {130},
	year = {2018},
	pages = {926-931},
	doi = {10.1016/j.procs.2018.04.091},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051268549\&doi=10.1016\%2fj.procs.2018.04.091\&partnerID=40\&md5=7c925e4f04388d1fe39f849c5b0c02f1},
	author = {Lachhab, F. and Bakhouya, M. and Ouladsine, R. and Essaaidi, M.}
}
