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Multi-room occupancy estimation through adaptive gray-box models
School of Electrical Engineering, KTH Royal Institute of Technology, ACCESS and the Department of Automatic Control, School of Electrical Engineering, KTH Royal Institute of Technology.
School of Electrical Engineering, KTH Royal Institute of Technology, ACCESS and the Department of Automatic Control, School of Electrical Engineering, KTH Royal Institute of Technology.
Kungliga tekniska högskolan, KTH, ACCESS and the Department of Automatic Control, School of Electrical Engineering, KTH Royal Institute of Technology.
School of Electrical Engineering, KTH Royal Institute of Technology, ACCESS and the Department of Automatic Control, School of Electrical Engineering, KTH Royal Institute of Technology.
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2015 (English)In: IEEE 54th Annual Conference on Decision and Control (CDC): Osaka, Japan, 15-18 Dec. 2015, Piscataway, NJ: IEEE Communications Society, 2015, 3705-3711 p., 7402794Conference paper (Refereed)
Abstract [en]

We consider the problem of estimating the occupancy level in buildings using indirect information such as CO2 concentrations and ventilation levels. We assume that one of the rooms is temporarily equipped with a device measuring the occupancy. Using the collected data, we identify a gray-box model whose parameters carry information about the structural characteristics of the room. Exploiting the knowledge of the same type of structural characteristics of the other rooms in the building, we adjust the gray-box model to capture the CO2 dynamics of the other rooms. Then the occupancy estimators are designed using a regularized deconvolution approach which aims at estimating the occupancy pattern that best explains the observed CO2 dynamics. We evaluate the proposed scheme through extensive simulation using a commercial software tool, IDA-ICE, for dynamic building simulation

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Communications Society, 2015. 3705-3711 p., 7402794
Series
, I E E E Conference on Decision and Control. Proceedings, ISSN 0743-1546
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-37438DOI: 10.1109/CDC.2015.7402794Local ID: b764aa94-f558-472f-aa21-29bce2b1f227ISBN: 978-1-4799-7886-1 (PDF)OAI: oai:DiVA.org:ltu-37438DiVA: diva2:1010936
Conference
IEEE Conference of Decision and Control : 16/12/2015 - 18/12/2015
Note
Godkänd; 2015; 20160418 (andbra)Available from: 2016-10-03 Created: 2016-10-03Bibliographically approved

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