Linearization in the Large of the Anaerobic Digestion Process Using a Reduced-Order Koopman Operator

The identification of accurate models for the anaerobic digestion process is essential for the characterization of the region that guarantees the conservation of the bacteria population. Traditional techniques involve the identification of nonlinear models based on data from the system. In this pape...

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Bibliographic Details
Published inIFAC-PapersOnLine Vol. 53; no. 2; pp. 16840 - 16845
Main Authors Garcia-Tenorio, Camilo, Sbarciog, Mihaela, Mojica-Nava, Eduardo, Wouwer, Alain Vande
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 2020
Subjects
Anaerobic Digestion
EDMD
Eigenfunction
Eigenvalue
Koopman Operator
Nonlinear Systems
Eigenvalue
Nonlinear Systems
Anaerobic Digestion
Eigenfunction
EDMD
Koopman Operator
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Summary:The identification of accurate models for the anaerobic digestion process is essential for the characterization of the region that guarantees the conservation of the bacteria population. Traditional techniques involve the identification of nonlinear models based on data from the system. In this paper, we introduce data-driven techniques that allow the characterization of the system’s behavior via the approximation of the Koopman operator with the extended dynamic mode decomposition algorithm. We propose methods to reduce the order and dimension of the representation based on orthogonal polynomials.
ISSN:2405-8963
2405-8963
DOI:10.1016/j.ifacol.2020.12.1184