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dc.contributor.authorAljehani, Fahad
dc.contributor.authorLaleg-Kirati, Taous-Meriem
dc.date.accessioned2020-12-23T11:09:05Z
dc.date.available2020-12-23T11:09:05Z
dc.date.issued2020-12-22
dc.date.submitted2020-09-13
dc.identifier.citationAljehani, F., & Laleg-Kirati, T.-M. (2021). Iterative Learning Based Modulating Functions Method for Distributed Solar Source Estimation. 2021 American Control Conference (ACC). doi:10.23919/acc50511.2021.9482958
dc.identifier.isbn9781665441971
dc.identifier.issn0743-1619
dc.identifier.doi10.23919/acc50511.2021.9482958
dc.identifier.doi10.1109/LCSYS.2020.3045939
dc.identifier.urihttp://hdl.handle.net/10754/666615
dc.description.abstractModulating functions method is a non asymptotic estimation method, which provides accurate and robust estimations of states, parameters and inputs for different classes of systems, which include unknown linear ordinary differential systems, fractional systems and linear partial differential equations. In the case of time or space varying unknown, the method requires the decomposition of the unknown into predefined basis functions. However, the estimation performance will depend on the nature of the basis functions which in some cases are not easy to determine. This paper proposes a new iterative learning based modulating functions method, which combines the standard modulating functions with a dictionary learning procedure. The dictionary learning step allows the determination of appropriate set of functions to decompose the unknown, while the modulating function step allows the nonasymptotic and robust estimation of the projection coefficients. The performance of the proposed method is illustrated in a distributed solar collector application, modeled by partial differential equations and where the unknown solar irradiance is estimated.
dc.description.sponsorshipThis work has been supported by the King Abdullah University of Science and Technology (KAUST), Base Research Fund (BAS/1/1627-01-01) to Taous Meriem Laleg.
dc.publisherIEEE
dc.relation.urlhttps://ieeexplore.ieee.org/document/9482958/
dc.rightsArchived with thanks to IEEE
dc.subjectDictionary learning
dc.subjectmodulating functions
dc.subjectnon-asymptotic estimation.
dc.titleIterative Learning Based Modulating Functions Method for Distributed Solar Source Estimation
dc.typeConference Paper
dc.typeArticle
dc.contributor.departmentElectrical Engineering Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentComputational Bioscience Research Center (CBRC)
dc.identifier.journalIEEE Control Systems Letters
dc.conference.date25-28 May 2021
dc.conference.name2021 American Control Conference (ACC)
dc.conference.locationNew Orleans, LA, USA
dc.eprint.versionPre-print
kaust.personAljehani, Fahad
kaust.personLaleg-Kirati, Taous-Meriem
kaust.grant.numberBAS/1/1627-01-01
refterms.dateFOA2021-01-19T06:01:09Z
kaust.acknowledged.supportUnitBase Research Fund


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