Application of an extended kalman filter for state estimation of yeast fermentation

verfasst von: K. H. Bellgardt, W. Kuhlmann, H. D. Meyer, K. Schuegerl, M. Thoma
Abstract: The development of a Kalman filter for state and parameter estimation of a biotechnical process is discussed. Because of the large complexity of biotechnical processes, mathematical models for online estimation are based on simplifications. Therefore model errors in the structure and parameters cannot be avoided. In such situations, simulations of the process in combination with the estimator are helpful during the design phase: these permit fast examinations of the different behaviour of linear filters compared to nonlinear algorithms and also investigations of the influence of sampling interval and initial values of state and filter variables on the estimation. By the use of such simulations, the suitability of process models with various degrees of simplifications can also be easily tested. Based on the simulations, an extended Kalman filter with iteration of the output equations was chosen. Besides the states, two parameters of a third order process model are estimated online.
Externe Organisation(en): Helmholtz-Zentrum für Infektionsforschung GmbH (HZI)
Typ: Artikel
Journal: IEE Proceedings D: Control Theory and Applications
Band: 133
Seiten: 226-234
Anzahl der Seiten: 9
ISSN: 0143-7054
Publikationsdatum: 1986
Publikationsstatus: Veröffentlicht
Peer-reviewed: Ja
ASJC Scopus Sachgebiete: Allgemeiner Maschinenbau
Elektronische Version(en): https://doi.org/10.1049/ip-d.1986.0037 (Zugang: Geschlossen)

BibTeX

@article{0e6e981a11aa4d628a8485c9d04a5d00,
title = "Application of an extended kalman filter for state estimation of yeast fermentation",
abstract = "The development of a Kalman filter for state and parameter estimation of a biotechnical process is discussed. Because of the large complexity of biotechnical processes, mathematical models for online estimation are based on simplifications. Therefore model errors in the structure and parameters cannot be avoided. In such situations, simulations of the process in combination with the estimator are helpful during the design phase: these permit fast examinations of the different behaviour of linear filters compared to nonlinear algorithms and also investigations of the influence of sampling interval and initial values of state and filter variables on the estimation. By the use of such simulations, the suitability of process models with various degrees of simplifications can also be easily tested. Based on the simulations, an extended Kalman filter with iteration of the output equations was chosen. Besides the states, two parameters of a third order process model are estimated online.",
author = "Bellgardt, {K. H.} and W. Kuhlmann and Meyer, {H. D.} and K. Schuegerl and M. Thoma",
year = "1986",
doi = "10.1049/ip-d.1986.0037",
language = "English",
volume = "133",
pages = "226--234",
journal = "IEE Proceedings D: Control Theory and Applications",
issn = "0143-7054",
publisher = "Institution of Electrical Engineers (IEE)",
number = "5",
}