363. 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 and C. Oliver Kappe; Journal of Process Control (2023); DOI: 10.1016/j.jprocont.2022.12.009
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.