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Application-oriented input design for room occupancy estimation algorithms
KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0003-0283-5717
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0002-1927-1690
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2017 (English)In: 2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2017Conference paper, Published paper (Refereed)
Abstract [en]

We consider the problem of occupancy estimation in buildings using available environmental information. In particular, we study the problem of how to collect data that is informative enough for occupancy estimation purposes. We thus propose an application-oriented input design approach for designing the ventilation signal to be used while collecting the system identification datasets. The main goal of the method is to guarantee a certain accuracy in the estimated occupancy levels while minimizing the experimental time and effort. To take into account potential limitations on the actuation signals we moreover formulate the problem as a recursive nonlinear and nonconvex optimization problem, solved then using exhaustive search methods. We finally corroborate the theoretical findings with some numerical examples, which results show that computing ventilation signals using experiment design concepts leads to occupancy estimator performing 4 times better in terms of Mean Square Error (MSE).

Place, publisher, year, edition, pages
IEEE , 2017.
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
Keywords [en]
Occupancy estimation, CO2 dynamics, application-oriented input design, minimum-time input design
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-223848ISI: 000424696903050ISBN: 978-1-5090-2873-3 OAI: oai:DiVA.org:kth-223848DiVA, id: diva2:1187947
Conference
IEEE 56th Annual Conference on Decision and Control (CDC), DEC 12-15, 2017, Melbourne, AUSTRALIA
Funder
Swedish Research Council
Note

QC 20180306

Available from: 2018-03-06 Created: 2018-03-06 Last updated: 2018-03-06Bibliographically approved

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Ebadat, AfroozWahlberg, BoJohansson, Karl H.

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CiteExportLink to record
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  • apa
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Output format
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