Control of a complex multistep process for the production of mesalazine

Ismael Castillo; Jakob Rehrl; Peter Sagmeister; René Lebl; Julia Kruisz; Selma Celikovic; Martin Sipek; Dirk Kirschneck; Martin Horn; Stephan Sacher; David Cantillo; Jason D. Williams; Johannes G. Khinast; C. Oliver Kappe

doi:10.1016/j.jprocont.2022.12.009

Control of a complex multistep process for the production of mesalazine

Ismael Castillo^*, Jakob Rehrl, Peter Sagmeister, René Lebl, Julia Kruisz, Selma Celikovic, Martin Sipek, Dirk Kirschneck, Martin Horn, Stephan Sacher, David Cantillo, Jason D. Williams, Johannes G. Khinast, C. Oliver Kappe

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

This paper presents the application of Data Driven Modelling (DDM) and Non-Linear Model Predictive Control (NMPC) for the control implementation of a continuous reactor for the production of the Active Pharmaceutical Ingredient (API), Mesalazine. The contribution of this work is to present the overall control architecture, the step-by-step controller design based on DDM, i.e. Neuro-Fuzzy/Local Linear Model Tree Models (LoLiMoT) and NMPC. We demonstrate the advantages of DDM and NMPC, in the presence of non-linear, distributed parameter, multi-variable systems as a suitable, powerful and practical way to approach complex process control challenges. Compared to conventional concepts, the inherent optimization structure of NMPC allows to obtain the desired behaviour of the multi-variable non-linear plant considering the physical constraints of operation regions. The control concept has been implemented in the real system on one central computer, XamControl (Evon), with all measurement devices and actuators centrally interconnected.

Original language	English
Pages (from-to)	59-68
Number of pages	10
Journal	Journal of Process Control
Volume	122
DOIs	https://doi.org/10.1016/j.jprocont.2022.12.009
Publication status	Published - Feb 2023

Keywords

Data driven models
LoLiMoT identification
Multi-step continuous flow process
Non-linear model predictive control
Synthesis of active pharmaceutical ingredient

ASJC Scopus subject areas

Control and Systems Engineering
Modelling and Simulation
Computer Science Applications
Industrial and Manufacturing Engineering

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10.1016/j.jprocont.2022.12.009

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title = "Control of a complex multistep process for the production of mesalazine",

abstract = "This paper presents the application of Data Driven Modelling (DDM) and Non-Linear Model Predictive Control (NMPC) for the control implementation of a continuous reactor for the production of the Active Pharmaceutical Ingredient (API), Mesalazine. The contribution of this work is to present the overall control architecture, the step-by-step controller design based on DDM, i.e. Neuro-Fuzzy/Local Linear Model Tree Models (LoLiMoT) and NMPC. We demonstrate the advantages of DDM and NMPC, in the presence of non-linear, distributed parameter, multi-variable systems as a suitable, powerful and practical way to approach complex process control challenges. Compared to conventional concepts, the inherent optimization structure of NMPC allows to obtain the desired behaviour of the multi-variable non-linear plant considering the physical constraints of operation regions. The control concept has been implemented in the real system on one central computer, XamControl (Evon), with all measurement devices and actuators centrally interconnected.",

keywords = "Data driven models, LoLiMoT identification, Multi-step continuous flow process, Non-linear model predictive control, Synthesis of active pharmaceutical ingredient",

author = "Ismael Castillo and Jakob Rehrl and Peter Sagmeister and Ren{\'e} Lebl and Julia Kruisz and Selma Celikovic and Martin Sipek and Dirk Kirschneck and Martin Horn and Stephan Sacher and David Cantillo and Williams, {Jason D.} and Khinast, {Johannes G.} and Kappe, {C. Oliver}",

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year = "2023",

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doi = "10.1016/j.jprocont.2022.12.009",

language = "English",

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T1 - Control of a complex multistep process for the production of mesalazine

AU - Castillo, Ismael

AU - Rehrl, Jakob

AU - Sagmeister, Peter

AU - Lebl, René

AU - Kruisz, Julia

AU - Celikovic, Selma

AU - Sipek, Martin

AU - Kirschneck, Dirk

AU - Horn, Martin

AU - Sacher, Stephan

AU - Cantillo, David

AU - Williams, Jason D.

AU - Khinast, Johannes G.

AU - Kappe, C. Oliver

PY - 2023/2

Y1 - 2023/2

N2 - This paper presents the application of Data Driven Modelling (DDM) and Non-Linear Model Predictive Control (NMPC) for the control implementation of a continuous reactor for the production of the Active Pharmaceutical Ingredient (API), Mesalazine. The contribution of this work is to present the overall control architecture, the step-by-step controller design based on DDM, i.e. Neuro-Fuzzy/Local Linear Model Tree Models (LoLiMoT) and NMPC. We demonstrate the advantages of DDM and NMPC, in the presence of non-linear, distributed parameter, multi-variable systems as a suitable, powerful and practical way to approach complex process control challenges. Compared to conventional concepts, the inherent optimization structure of NMPC allows to obtain the desired behaviour of the multi-variable non-linear plant considering the physical constraints of operation regions. The control concept has been implemented in the real system on one central computer, XamControl (Evon), with all measurement devices and actuators centrally interconnected.

AB - This paper presents the application of Data Driven Modelling (DDM) and Non-Linear Model Predictive Control (NMPC) for the control implementation of a continuous reactor for the production of the Active Pharmaceutical Ingredient (API), Mesalazine. The contribution of this work is to present the overall control architecture, the step-by-step controller design based on DDM, i.e. Neuro-Fuzzy/Local Linear Model Tree Models (LoLiMoT) and NMPC. We demonstrate the advantages of DDM and NMPC, in the presence of non-linear, distributed parameter, multi-variable systems as a suitable, powerful and practical way to approach complex process control challenges. Compared to conventional concepts, the inherent optimization structure of NMPC allows to obtain the desired behaviour of the multi-variable non-linear plant considering the physical constraints of operation regions. The control concept has been implemented in the real system on one central computer, XamControl (Evon), with all measurement devices and actuators centrally interconnected.

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ER -

Control of a complex multistep process for the production of mesalazine

Abstract

Keywords

ASJC Scopus subject areas

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