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

authored by: 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.
External Organisation(s): Helmholtz Centre for Infection Research (HZI)
Type: Article
Journal: IEE Proceedings D: Control Theory and Applications
Volume: 133
Pages: 226-234
No. of pages: 9
ISSN: 0143-7054
Publication date: 1986
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: General Engineering
Electronic version(s): https://doi.org/10.1049/ip-d.1986.0037 (Access: Closed)

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",
}