Details
| Original language | English |
|---|---|
| Pages (from-to) | 226-234 |
| Number of pages | 9 |
| Journal | IEE Proceedings D: Control Theory and Applications |
| Volume | 133 |
| Issue number | 5 |
| Publication status | Published - 1986 |
| Externally published | Yes |
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.
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In: IEE Proceedings D: Control Theory and Applications, Vol. 133, No. 5, 1986, p. 226-234.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Application of an extended kalman filter for state estimation of yeast fermentation
AU - Bellgardt, K. H.
AU - Kuhlmann, W.
AU - Meyer, H. D.
AU - Schuegerl, K.
AU - Thoma, M.
PY - 1986
Y1 - 1986
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=0022780718&partnerID=8YFLogxK
U2 - 10.1049/ip-d.1986.0037
DO - 10.1049/ip-d.1986.0037
M3 - Article
AN - SCOPUS:0022780718
VL - 133
SP - 226
EP - 234
JO - IEE Proceedings D: Control Theory and Applications
JF - IEE Proceedings D: Control Theory and Applications
SN - 0143-7054
IS - 5
ER -