Modeling and fuzzy optimization of fed-batch Fermentation process

An optimal substrate feeding strategy for a laboratory scale fed-batch bioreactor is determined through non-iterative fuzzy, optimization in order to maximize the cell-mass production. Adequate model for laboratory scale of E. Coli fermentation is developed and the model parameters for an effective and reliable description of the reactor dynamics are identified. Statistical validity of the model indicated the confidence in a prediction of the model. The objective function for optimization is maximized with non-iterative fuzzy optimization with respect to the sugar feed rate. The resulting optimal policy indicated considerable increase in the biomass and shows that this approach can be applied with success for optimization of bioprocesses.