Moment-based Kalman Filter design for cell population balance models in batch fermentation processes⁎Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project-ID 395461267. Issue 3 (2021)

• Record Type: Journal Article
• Authors: Jerono, P.; Schaum, A.; Meurer, T.
• Is Part Of: IFAC-PapersOnLine. Volume 54:Issue 3(2021)
• Page Start: 19
• Page End: 24
• Publication Date: 2021
• Subjects: Cell population balance models -- partial integro-differential equation -- yeast fermentation -- process control -- Kalman filtering -- moments of a distribution; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2021.08.212
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: The observer design problem for the cell population estimation in a yeast batch process is addressed. The cell population balance model is described by a partial integro-differential equation coupled with a set of ordinary differential equations. Based on the observability property of the first moment of the cell distribution and the structural observability of the discretized cell population balance model, an extended Kalman Filter operating on online biomass measurements is designed for the model equations. The observer is validated using experimental data.