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Experimental adaptive on-line optimization of cellular productivity of a continuous bakers' yeast culture
1School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47907.
Abstract:
An adaptive on-line optimization method that utilizes dynamic model identification has been applied to maximize the cellular productivity of a continuous bakers' yeast culture. Experiments were conducted on a sophisticated computerized fermentation system. Experimental results show that the adaptive on-line optimization method requires very little a priori information, is easy to implement, converges quickly, adapts to changes in the process, and is stable even when operational difficulties are encountered.
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