Comparison of different state estimator algorithms applied to a simulated anaerobic digestion reactor

Autor:	Shadi Attar, Finn Haugen
Rok vydání:	2018
Předmět:	Anaerobic digestion Computer science State estimator Kalman filter Particle filter Algorithm
Zdroj:	Linköping Electronic Conference Proceedings
ISSN:	1650-3686
DOI:	10.3384/ecp18153118
Popis:	This study deals with a simulator-based comparison of different state estimators of an anaerobic digestion process. A simulated biogas reactor based on the AM2 model is considered. Extended Kalman Filter, Unscented Kalman Filter, Particle Filter and Moving Horizon Estimator are four state estimators studied. The investigation is on both states and parameters estimation. The maximum number of parameters can be estimated equals the number of the measurement. Comparison of different state estimator algorithms applied to a simulated anaerobic digestion reactor
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::006bc2fc26a2fa96bb85b7a50ab59c0b https://doi.org/10.3384/ecp18153118 Zobrazit plný text záznamu