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  • 标题:Model Predictive Control of a Fed-batch Bioreactor Based on Dynamic Metabolic-Genetic Network Models
  • 本地全文:下载
  • 作者:Banafsheh Jabarivelisdeh ; Rolf Findeisen ; Steffen Waldherr
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2018
  • 卷号:51
  • 期号:19
  • 页码:34-37
  • DOI:10.1016/j.ifacol.2018.09.029
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn this work, a model predictive control of a fed-batch bioreactor is presented, described by the dynamic enzyme-cost FBA model (deFBA). The deFBA model is employed within a bilevel optimization to obtain fed-batch operating policies including the substrate feeding and process-level regulation of metabolism for optimizing the productivity of a target product. The advantages of implementing the closed-loop control in order to compensate for modelling errors are evaluated by comparing with the performance of an open-loop control. A case study involving the fed-batch fermentationof Escherichia colifor ethanol production is considered to find optimal operating strategies for maximal productivity.
  • 关键词:KeywordsModel Predictive ControlFed-batch bioreactorDynamic enzyme-cost FBA modelBilevel optimizationProductivity
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