Project Details
Projekt
Adaptive Optimal Control of Continuous Aqueous Two-Phase Flotation (ATPF)
Subject Area
Mechanical Process Engineering
Term
since 2022
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 504452366
The relevance of enzymes in the biotechnology industry has increased significantly in recent years. Until now, biosynthesis in continuous fermentation processes in the industry has been followed by a complex downstream process to separate and purify the enzymes from the fermentation broth. Conventional purification processes are not only energy and cost intensive due to the large number of individual process steps, but long residence times also lead to losses in product quality and yield. The aim of this project is to develop an alternative process chain for enzyme recovery. The first process step is continuous aqueous two-phase flotation (ATPF), which was the focus of the first funding period of the SPP. An ATPF laboratory plant was first equipped with online measurement technology to characterize the process behavior. This allowed the identification of two different system models, a black-box model and a mechanistic dynamic model. Based on these system models, a predictive closed-loop control system was developed for ATPF, which allows to maximize the separation efficiency by adjusting the process parameters (i.e. the gas volume flows of the gassing units and the top and bottom phase volume flows). To further concentrate the enzyme-loaded top phase from the ATPF, the development of a process chain with an subsequent ultrafiltration (UF) unit is planned for the second funding period. An autonomous and robust control strategy for the UF unit and the entire process chain will be developed. A particular challenge is the interdependence of the process steps, which can lead to disturbances and must be taken into account in the development of the controller. The experimental work will be carried out at the Institute of Mechanical Process Engineering and Mechanics at the Karlsruhe Institute of Technology (KIT, Prof. Hermann Nirschl), including the establishment of online measurement technology to monitor enzyme yield and activity, and the process characterization at varying process parameters. In combination with known correlations from the literature, the KIT group develops a mechanistic system model for UF. The Department of Microsystems Engineering at the University of Freiburg (UFR, Prof. Moritz Diehl) develops a black-box model and a predictive control strategy based on the identified system models. The validation and adaption of the closed-loop control system for the UF and the entire process chain will be done in close cooperation between the two working groups.
DFG Programme
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