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On the Use of Nonlinear Model Predictive Control without Parameter Adaptation for Batch Processes
Open AccessFeature PaperArticle

Combined Estimation and Optimal Control of Batch Membrane Processes

1
Faculty of Chemical and Food Technology, Slovak University of Technology in Bratislava, Radlinskeho 9, 81237 Bratislava, Slovakia
2
Department of Chemical and Biochemical Engineering, Technische Universität Dortmund, Emil-Figge-Strasse 70, 44221 Dortmund, Germany
3
Laboratoire Réactions et Génie des Procédés, CNRS-ENSIC, Université de Lorraine, 1 rue Grandville, 54001 Nancy, France
*
Author to whom correspondence should be addressed.
Academic Editor: Dominique Bonvin
Processes 2016, 4(4), 43; https://doi.org/10.3390/pr4040043
Received: 13 October 2016 / Revised: 8 November 2016 / Accepted: 10 November 2016 / Published: 18 November 2016
(This article belongs to the Special Issue Real-Time Optimization)
In this paper, we deal with the model-based time-optimal operation of a batch diafiltration process in the presence of membrane fouling. Membrane fouling poses one of the major problems in the field of membrane processes. We model the fouling behavior and estimate its parameters using various methods. Least-squares, least-squares with a moving horizon, recursive least-squares methods and the extended Kalman filter are applied and discussed for the estimation of the fouling behavior on-line during the process run. Model-based optimal non-linear control coupled with parameter estimation is applied in a simulation case study to show the benefits of the proposed approach. View Full-Text
Keywords: batch diafiltration; membrane fouling; time-optimal operation; fouling estimation batch diafiltration; membrane fouling; time-optimal operation; fouling estimation
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MDPI and ACS Style

Jelemenský, M.; Pakšiová, D.; Paulen, R.; Latifi, A.; Fikar, M. Combined Estimation and Optimal Control of Batch Membrane Processes. Processes 2016, 4, 43.

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