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    Iterative Learning Based Modulating Functions Method for Distributed Solar Source Estimation

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    LCSYS3045939.pdf
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    Type
    Article
    Authors
    Aljehani, Fahad
    Laleg-Kirati, Taous-Meriem cc
    KAUST Department
    Electrical Engineering Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Computational Bioscience Research Center (CBRC)
    KAUST Grant Number
    BAS/1/1627-01-01
    Date
    2020-12-22
    Submitted Date
    2020-09-13
    Permanent link to this record
    http://hdl.handle.net/10754/666615
    
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    Abstract
    Modulating 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 non-asymptotic 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.
    Citation
    Aljehani, F., & Laleg-Kirati, T.-M. (2020). Iterative Learning Based Modulating Functions Method for Distributed Solar Source Estimation. IEEE Control Systems Letters, 1–1. doi:10.1109/lcsys.2020.3045939
    Sponsors
    This 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.
    Publisher
    IEEE
    Journal
    IEEE Control Systems Letters
    DOI
    10.1109/LCSYS.2020.3045939
    Additional Links
    https://ieeexplore.ieee.org/document/9302746/
    https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9302746
    ae974a485f413a2113503eed53cd6c53
    10.1109/LCSYS.2020.3045939
    Scopus Count
    Collections
    Articles; Electrical Engineering Program; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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