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Analysis, Online Estimation, and Validation of a Competing Virus Model
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0002-4095-7320
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0001-8942-2880
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0003-1835-2963
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0001-9940-5929
2020 (English)In: 2020 American Control Conference (ACC), Institute of Electrical and Electronics Engineers (IEEE), 2020, p. 2556-2561, article id 9147568Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we introduce a discrete time competing virus model and the assumptions necessary for the model to be well posed. We analyze the system exploring its different equilibria. We provide necessary and sufficient conditions for the estimation of the model parameters from time series data and introduce an online estimation algorithm. We employ a dataset of two competing subsidy programs from the US Department of Agriculture to validate the model by employing the identification techniques. To the best of our knowledge, this work is the first to study competing virus models in discretetime, online identification of spread parameters from time series data, and validation of said models using real data. These new contributions are important for applications since real data is naturally sampled.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2020. p. 2556-2561, article id 9147568
Series
Proceedings of the American Control Conference, ISSN 0743-1619
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-292384DOI: 10.23919/ACC45564.2020.9147568ISI: 000618079802085Scopus ID: 2-s2.0-85085256492OAI: oai:DiVA.org:kth-292384DiVA, id: diva2:1541304
Conference
2020 American Control Conference, ACC 2020; Denver; United States; 1 July 2020 through 3 July 2020
Note

QC 20210331

Available from: 2021-03-31 Created: 2021-03-31 Last updated: 2023-04-05Bibliographically approved

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Pare, Philip E.Vrabac, DamirSandberg, HenrikJohansson, Karl H.

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  • apa
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