Optimization of Substrate Feed Flow Rate for Fed-Batch Yeast Fermentation Process

This paper presents Q-Learning (QL) algorithm based on optimization method to determine optimal glucose feed flow rate profile for the yeast fermentation process. The optimal profile is able to maximize the yeast concentration at the end of the process, meanwhile to minimize the formation of ethanol during the process. The proposed approach is tested under four case studies, which are different in initial yeast and glucose concentration. The results show that the proposed approach is able to control the process in a satisfactory way.