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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 tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.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.
Vise andre og tillknytning
2018 (engelsk)Inngår i: 2017 IEEE 56th Conference on Decision and Control, CDC, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2018, s. 3417-3424Konferansepaper, Publicerat paper (Fagfellevurdert)
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).

sted, utgiver, år, opplag, sider
Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2018. s. 3417-3424
Serie
IEEE Conference on Decision and Control, E-ISSN 0743-1546
HSV kategori
Forskningsprogram
Reglerteknik
Identifikatorer
URN: urn:nbn:se:ltu:diva-67654DOI: 10.1109/CDC.2017.8264159ISI: 000424696903050Scopus ID: 2-s2.0-85046132323ISBN: 978-1-5090-2873-3 (digital)ISBN: 978-1-5090-2874-0 (tryckt)OAI: oai:DiVA.org:ltu-67654DiVA, id: diva2:1182716
Konferanse
56th IEEE Conference on Decision and Control, CDC 2017, Melbourne, VIC, Australia , 12-15 December 2017
Tilgjengelig fra: 2018-02-14 Laget: 2018-02-14 Sist oppdatert: 2019-05-06bibliografisk kontrollert

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