Abstract
An algorithm for the optimization of a fermentation process was investigated using the combination of dynamic programming and a linear predictive procedure by regression analysis. It was applied to the fed-batch culture for glutamic acid production with ethanol feeding and was proved to be effective for solving the optimization problems including online adaptive control. The effect of linear predictive error on the optimum policy was discussed by use of Fishman and Biryukov’s model of penicillin production. The prediction method was modified for application to processes including unmeasurable state variables. The use of time-series data was proved to be effective for prediction of a fed-batch culture of baker’s yeast.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
