Publication | Closed Access
Optimal Experimental Design for Parameter Estimation in Unstructured Growth Models
133
Citations
12
References
1994
Year
Parameter EstimationEngineeringBioenergyAgricultural EconomicsOptimal Experimental DesignParameter IdentificationNumerical SimulationModel ValidityModeling And SimulationFood Process EngineeringEstimation TheoryStatisticsHealth SciencesBiomass UtilizationProcess DesignKinetic ParametersProcess EngineeringPopulation Balance ModelingProcess Simulation ModelProcess ControlGrowth TheorySeed ProcessingMultiscale Modeling
Abstract A method of optimal experimental design for parameter estimation in unstructured growth models is presented. The approach is based on a method suggested by Munack (1991) for application in fed‐batch processes. In a critical analysis of this method, special emphasis is given to the model validity, because unstructured growth models often are not valid under transient conditions. In consequence, a combined object function has been introduced, which considers model validity and the accuracy of the kinetic parameters to be estimated. The application of this method for fed‐batch processes leads to satisfactory results. Investigations of different fed‐batch strategies regarding model validity and the quality of parameter estimation are presented. In addition, an experimental verification has been performed with fermentations of the yeast Trichosporon cutaneum .
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