The Extended Kalman Filter for Nonlinear State Estimation in a U-loop Bioreactor

Tobias K. S. Ritschel; Dimitri Boiroux; Marcus Krogh Nielsen; Jakob Kjøbsted Huusom; Sten Bay Jørgensen; John Bagterp Jørgensen

doi:10.1109/ccta.2019.8920643

The Extended Kalman Filter for Nonlinear State Estimation in a U-loop Bioreactor

Tobias K. S. Ritschel, Dimitri Boiroux, Marcus Krogh Nielsen, Jakob Kjøbsted Huusom, Sten Bay Jørgensen, John Bagterp Jørgensen^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

In this paper, we consider nonlinear state estimation in the U-loop reactor for single-cell protein (SCP) production. The model of the U-loop reactor is a mixture of stochastic partial differential equations and stochastic differential equations which are stiff. By a typical finite-volume spatial discretization, the resulting system of stochastic differential equations for numerical simulation and state estimation has 83 states. We investigate and discuss the continuous-discrete EKF for state estimation in this high-dimensional and stiff continuous-discrete-time system.

Original language	English
Title of host publication	2019 IEEE Conference on Control Technology and Applications (CCTA)
Publisher	IEEE
Publication date	2019
Pages	920-925
ISBN (Print)	978-1-7281-2768-2
ISBN (Electronic)	978-1-7281-2767-5
DOIs	https://doi.org/10.1109/ccta.2019.8920643
Publication status	Published - 2019
Event	2019 IEEE Conference on Control Technology and Applications - City University of Hong Kong, Hong Kong, China Duration: 19 Aug 2019 → 21 Aug 2019 Conference number: 3 https://ccta2019.ieeecss.org/

Conference

Conference	2019 IEEE Conference on Control Technology and Applications
Number	3
Location	City University of Hong Kong
Country/Territory	China
City	Hong Kong
Period	19/08/2019 → 21/08/2019
Sponsor	City University of Hong Kong, Hong Kong Automatic Control Association, IEEE
Internet address	https://ccta2019.ieeecss.org/

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@inproceedings{d802e11c5d3e47d293f965fb7b0c90ce,

title = "The Extended Kalman Filter for Nonlinear State Estimation in a U-loop Bioreactor",

abstract = "In this paper, we consider nonlinear state estimation in the U-loop reactor for single-cell protein (SCP) production. The model of the U-loop reactor is a mixture of stochastic partial differential equations and stochastic differential equations which are stiff. By a typical finite-volume spatial discretization, the resulting system of stochastic differential equations for numerical simulation and state estimation has 83 states. We investigate and discuss the continuous-discrete EKF for state estimation in this high-dimensional and stiff continuous-discrete-time system.",

author = "Ritschel, {Tobias K. S.} and Dimitri Boiroux and Nielsen, {Marcus Krogh} and Huusom, {Jakob Kj{\o}bsted} and J{\o}rgensen, {Sten Bay} and J{\o}rgensen, {John Bagterp}",

year = "2019",

doi = "10.1109/ccta.2019.8920643",

language = "English",

isbn = "978-1-7281-2768-2",

pages = "920--925",

booktitle = "2019 IEEE Conference on Control Technology and Applications (CCTA)",

publisher = "IEEE",

address = "United States",

note = "2019 IEEE Conference on Control Technology and Applications, CCTA 2019 ; Conference date: 19-08-2019 Through 21-08-2019",

url = "https://ccta2019.ieeecss.org/",

}

Ritschel, TKS, Boiroux, D, Nielsen, MK, Huusom, JK, Jørgensen, SB & Jørgensen, JB 2019, The Extended Kalman Filter for Nonlinear State Estimation in a U-loop Bioreactor. in 2019 IEEE Conference on Control Technology and Applications (CCTA). IEEE, pp. 920-925, 2019 IEEE Conference on Control Technology and Applications, Hong Kong, China, 19/08/2019. https://doi.org/10.1109/ccta.2019.8920643

TY - GEN

T1 - The Extended Kalman Filter for Nonlinear State Estimation in a U-loop Bioreactor

AU - Ritschel, Tobias K. S.

AU - Boiroux, Dimitri

AU - Nielsen, Marcus Krogh

AU - Huusom, Jakob Kjøbsted

AU - Jørgensen, Sten Bay

AU - Jørgensen, John Bagterp

N1 - Conference code: 3

PY - 2019

Y1 - 2019

N2 - In this paper, we consider nonlinear state estimation in the U-loop reactor for single-cell protein (SCP) production. The model of the U-loop reactor is a mixture of stochastic partial differential equations and stochastic differential equations which are stiff. By a typical finite-volume spatial discretization, the resulting system of stochastic differential equations for numerical simulation and state estimation has 83 states. We investigate and discuss the continuous-discrete EKF for state estimation in this high-dimensional and stiff continuous-discrete-time system.

AB - In this paper, we consider nonlinear state estimation in the U-loop reactor for single-cell protein (SCP) production. The model of the U-loop reactor is a mixture of stochastic partial differential equations and stochastic differential equations which are stiff. By a typical finite-volume spatial discretization, the resulting system of stochastic differential equations for numerical simulation and state estimation has 83 states. We investigate and discuss the continuous-discrete EKF for state estimation in this high-dimensional and stiff continuous-discrete-time system.

U2 - 10.1109/ccta.2019.8920643

DO - 10.1109/ccta.2019.8920643

M3 - Article in proceedings

SN - 978-1-7281-2768-2

SP - 920

EP - 925

BT - 2019 IEEE Conference on Control Technology and Applications (CCTA)

PB - IEEE

T2 - 2019 IEEE Conference on Control Technology and Applications

Y2 - 19 August 2019 through 21 August 2019

ER -

The Extended Kalman Filter for Nonlinear State Estimation in a U-loop Bioreactor

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