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Adaptive exact linearization control of batch polymerization reactors using a Sigma-Point Kalman Filter

  • The Chylla–Haase polymerization reactor is widely accepted as a benchmark process for the evaluation of control strategies for batch reactors. In this contribution a control concept based on Exact I/O-Linearization is proposed and compared to a conventional cascade control structure. In order to adapt the exact linearization control strategy to various polymerization products and batch conditions, an advanced probabilistic inference algorithm (Sigma-Point Kalman Filter) is applied and investigated. Sigma-Point Kalman Filters have the major improvement of simplified implementation compared to local linearization methods (i.e. Extended Kalman Filter) because no analytical Jacobians are required. Stochastic simulation studies are introduced and show the effectiveness, accuracy and benefit of the control concept. Within several scenarios a satisfying robustness against structural errors in the underlying model equations for the nonlinear control law and the inference algorithm isThe Chylla–Haase polymerization reactor is widely accepted as a benchmark process for the evaluation of control strategies for batch reactors. In this contribution a control concept based on Exact I/O-Linearization is proposed and compared to a conventional cascade control structure. In order to adapt the exact linearization control strategy to various polymerization products and batch conditions, an advanced probabilistic inference algorithm (Sigma-Point Kalman Filter) is applied and investigated. Sigma-Point Kalman Filters have the major improvement of simplified implementation compared to local linearization methods (i.e. Extended Kalman Filter) because no analytical Jacobians are required. Stochastic simulation studies are introduced and show the effectiveness, accuracy and benefit of the control concept. Within several scenarios a satisfying robustness against structural errors in the underlying model equations for the nonlinear control law and the inference algorithm is demonstrated. Furthermore it is pointed out, that with little effort in reassembling the plant design, control performance can be improved significantly.show moreshow less

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Metadaten
Author:Marc-André Beyer, Wolfgang Grote, Gunter Reinig
Qualitätssicherung:peer reviewed
Fachbereich/Einrichtung:Hochschule Düsseldorf / Fachbereich - Maschinenbau und Verfahrenstechnik
Document Type:Article
Year of Completion:2008
Language of Publication:English
Publisher:Elsevier
Parent Title (English):Journal of Process Control
Volume:18
Issue:7-8
Page Number:13
First Page:663
Last Page:675
Related URL:http://1873-2771
DOI:https://doi.org/10.1016/j.jprocont.2007.12.002
Tag:Batch process operation; Exact I/O-Linearization control; Online parameter estimation; Sigma-Point Kalman Filter
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften / 620 Ingenieurwissenschaften und zugeordnete Tätigkeiten
Licence (German):keine Lizenz - nur Metadaten
Release Date:2024/02/02
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