Iterative Learning Based Modulating Functions Method for Distributed Solar Source Estimation
Type
ArticleKAUST Department
Electrical Engineering ProgramComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Computational Bioscience Research Center (CBRC)
KAUST Grant Number
BAS/1/1627-01-01Date
2020-12-22Submitted Date
2020-09-13Permanent link to this record
http://hdl.handle.net/10754/666615
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Show full item recordAbstract
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.2020.3045939Sponsors
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
IEEEJournal
IEEE Control Systems LettersAdditional Links
https://ieeexplore.ieee.org/document/9302746/https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9302746
ae974a485f413a2113503eed53cd6c53
10.1109/LCSYS.2020.3045939