Nonlinear control strategies for a micro-aerobic, fermentation process
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In this paper, we propose a new strategy to control the yield and productivity of the fermentation process by viewing the fermentation process as a multi-scale process, where the mixing conditions in terms of aeration rate and stirrer speed are considered in studying the bioreactor dynamics. The inclusion of mixing for bioreactor control would allow us to influence the metabolic activities of microorganisms through the distribution of nutrients to the microbial cells. The engagement of both mixing and biological processes, however, would lead to a very complex dynamics of the bioreactor. As a result, the control strategy with a direct use of a nonlinear model will be implemented. Two different modeling techniques to capture the mixing dynamics, namely data-based and kinetics hybrid modeling are proposed. The validated nonlinear models are used in determining the optimal aeration rate and stirrer speed to maintain the desired productivity and yield of the fermentation process for different disturbance scenarios via extensive simulation studies.
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