Moment-based Kalman Filter design for cell population balance models in batch fermentation processes
P. Jerono, Alexander Schaum, Thomas Meurer
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.
Topics & Concepts
ObservabilityPopulation balance equationKalman filterControl theory (sociology)Extended Kalman filterPopulationObserver (physics)Ordinary differential equationMoment (physics)MathematicsDiscretizationPartial differential equationAlpha beta filterApplied mathematicsDifferential equationMathematical optimizationComputer scienceStatisticsMathematical analysisMoving horizon estimationPhysicsArtificial intelligenceClassical mechanicsQuantum mechanicsControl (management)SociologyDemographyGene Regulatory Network AnalysisViral Infectious Diseases and Gene Expression in InsectsMicrobial Metabolic Engineering and Bioproduction