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Application-oriented input design for room occupancy estimation algorithms
ACCESS and the Department of Automatic Control, School of Electrical Engineering, KTH Royal Institute of Technology, Sweden.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-4310-7938
TU Eindhoven, Department of Electrical Engineering, Eindhoven, The Netherlands.
ACCESS and the Department of Automatic Control, School of Electrical Engineering, KTH Royal Institute of Technology, Sweden.
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2018 (English)In: 2017 IEEE 56th Conference on Decision and Control, CDC, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 3417-3424Conference 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
Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2018. p. 3417-3424
Series
IEEE Conference on Decision and Control, E-ISSN 0743-1546
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-67654DOI: 10.1109/CDC.2017.8264159ISI: :000424696903050Scopus ID: 2-s2.0-85046132323ISBN: 978-1-5090-2873-3 (electronic)ISBN: 978-1-5090-2874-0 (print)OAI: oai:DiVA.org:ltu-67654DiVA, id: diva2:1182716
Conference
56th IEEE Conference on Decision and Control, CDC 2017, Melbourne, VIC, Australia , 12-15 December 2017
Available from: 2018-02-14 Created: 2018-02-14 Last updated: 2018-05-09Bibliographically approved

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Ebadat, AfroozVaragnolo, Damiano

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  • apa
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