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Robust State and Input Estimation with Enhanced Convergence Rate for Monitoring Anaerobic Digestion

  • In this study, an observer for estimating the state and unknown inputs is proposed for monitoring anaerobic digestion processes. This estimator is based on a dynamic model considering acidogenesis and methanogenesis, and consists of three sub-observers: (a) a gramian-based fixed-time convergent observer for the inlet chemical oxygen demand (COD) and the acidogenic bacteria population, (b) an asymptotic observer for the methanogenic bacteria population, and (c) a super-twisting observer for systems with time-varying parameters to estimate the inlet volatile fatty acid (VFA) concentration. These sub-observers can be designed independently, which greatly simplifies the tuning process. Proofs of convergence are developed and simulation tests show the performance of the estimation scheme as compared to classical extended Kalman filtering.

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Metadaten
Author: Juan G. Rueda-EscobedoORCiD, Mihaela SbarciogORCiD, Jaime A. Moreno, Jan Van ImpeORCiD, Alain Vande Wouwer
URL:https://www.sciencedirect.com/science/article/pii/S0959152422001421
DOI:https://doi.org/10.1016/j.jprocont.2022.07.014
ISSN:0959-1524
Title of the source (English):Journal of Process Control
Document Type:Scientific journal article peer-reviewed
Language:English
Year of publication:2022
Volume/Year:117
Issue number:4
First Page:169
Last Page:180
Faculty/Chair:Fakultät 3 Maschinenbau, Elektro- und Energiesysteme / FG Regelungssysteme und Netzleittechnik
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