State and Input Estimation of Nonlinear Chromatographic Processes

Alexander Hørsholt; Lasse Hjuler Christiansen; Tobias Kasper Ritschel; Kristian Meyer; Jakob Kjøbsted Huusom; John Bagterp Jørgensen

doi:10.1109/ccta.2019.8920651

State and Input Estimation of Nonlinear Chromatographic Processes

Alexander Hørsholt, Lasse Hjuler Christiansen, Tobias Kasper Ritschel, Kristian Meyer, Jakob Kjøbsted Huusom, John Bagterp Jørgensen^*

^*Corresponding author for this work

Technical University of Denmark

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

Abstract

We investigate two algorithms for state estimation of nonlinear chromatographic processes: the Extended Kalman Filter and the Ensemble Kalman Filter. We consider the Equilibrium Dispersive Model for modeling of packed-bed chromatography. The Equilibrium Dispersive Model is governed by a convection-dominated nonlinear partial differential equation. The model is discretized by a high-order discontinuous-Galerkin finite-element method for accurate and efficient simulation of the chromatographic process. The discretization leads to a stochastic continuous-discrete model, and we use the Extended Kalman Filter and the Ensemble Kalman Filter for state estimation of the packed-bed chromatographic model. The performance and capabilities of both filters are demonstrated in simultaneous estimation of the unknown system states and uncertain inlet concentration.

Original language	English
Title of host publication	2019 IEEE Conference on Control Technology and Applications (CCTA)
Number of pages	6
Publisher	IEEE
Publication date	2019
Pages	1030-1035
ISBN (Print)	978-1-7281-2768-2
ISBN (Electronic)	978-1-7281-2767-5
DOIs	https://doi.org/10.1109/ccta.2019.8920651
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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10.1109/ccta.2019.8920651

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title = "State and Input Estimation of Nonlinear Chromatographic Processes",

abstract = "We investigate two algorithms for state estimation of nonlinear chromatographic processes: the Extended Kalman Filter and the Ensemble Kalman Filter. We consider the Equilibrium Dispersive Model for modeling of packed-bed chromatography. The Equilibrium Dispersive Model is governed by a convection-dominated nonlinear partial differential equation. The model is discretized by a high-order discontinuous-Galerkin finite-element method for accurate and efficient simulation of the chromatographic process. The discretization leads to a stochastic continuous-discrete model, and we use the Extended Kalman Filter and the Ensemble Kalman Filter for state estimation of the packed-bed chromatographic model. The performance and capabilities of both filters are demonstrated in simultaneous estimation of the unknown system states and uncertain inlet concentration.",

author = "Alexander H{\o}rsholt and Christiansen, {Lasse Hjuler} and Ritschel, {Tobias Kasper} and Kristian Meyer and Huusom, {Jakob Kj{\o}bsted} and J{\o}rgensen, {John Bagterp}",

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doi = "10.1109/ccta.2019.8920651",

language = "English",

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

publisher = "IEEE",

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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/",

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Hørsholt, A, Christiansen, LH, Ritschel, TK, Meyer, K, Huusom, JK & Jørgensen, JB 2019, State and Input Estimation of Nonlinear Chromatographic Processes. in 2019 IEEE Conference on Control Technology and Applications (CCTA). IEEE, pp. 1030-1035, 2019 IEEE Conference on Control Technology and Applications, Hong Kong, China, 19/08/2019. https://doi.org/10.1109/ccta.2019.8920651

TY - GEN

T1 - State and Input Estimation of Nonlinear Chromatographic Processes

AU - Hørsholt, Alexander

AU - Christiansen, Lasse Hjuler

AU - Ritschel, Tobias Kasper

AU - Meyer, Kristian

AU - Huusom, Jakob Kjøbsted

AU - Jørgensen, John Bagterp

N1 - Conference code: 3

PY - 2019

Y1 - 2019

N2 - We investigate two algorithms for state estimation of nonlinear chromatographic processes: the Extended Kalman Filter and the Ensemble Kalman Filter. We consider the Equilibrium Dispersive Model for modeling of packed-bed chromatography. The Equilibrium Dispersive Model is governed by a convection-dominated nonlinear partial differential equation. The model is discretized by a high-order discontinuous-Galerkin finite-element method for accurate and efficient simulation of the chromatographic process. The discretization leads to a stochastic continuous-discrete model, and we use the Extended Kalman Filter and the Ensemble Kalman Filter for state estimation of the packed-bed chromatographic model. The performance and capabilities of both filters are demonstrated in simultaneous estimation of the unknown system states and uncertain inlet concentration.

AB - We investigate two algorithms for state estimation of nonlinear chromatographic processes: the Extended Kalman Filter and the Ensemble Kalman Filter. We consider the Equilibrium Dispersive Model for modeling of packed-bed chromatography. The Equilibrium Dispersive Model is governed by a convection-dominated nonlinear partial differential equation. The model is discretized by a high-order discontinuous-Galerkin finite-element method for accurate and efficient simulation of the chromatographic process. The discretization leads to a stochastic continuous-discrete model, and we use the Extended Kalman Filter and the Ensemble Kalman Filter for state estimation of the packed-bed chromatographic model. The performance and capabilities of both filters are demonstrated in simultaneous estimation of the unknown system states and uncertain inlet concentration.

U2 - 10.1109/ccta.2019.8920651

DO - 10.1109/ccta.2019.8920651

M3 - Article in proceedings

SN - 978-1-7281-2768-2

SP - 1030

EP - 1035

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 -

State and Input Estimation of Nonlinear Chromatographic Processes

Abstract

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