Biochemical reactor modeling and control
Michael A. Henson
Abstract
Michael A. Henson
Abstract
Process control is expected to play an increasingly important role in the biotechnology industry. The development of feedback control systems that exploit advances in online measurement technology to achieve optimal productivity of continuous and fed-batch bioreactors is one of the most important challenges in biochemical manufacturing. This article provides an overview of current and emerging bioreactor control strategies based on unstructured dynamic models of cell growth and product formation. Despite their widespread acceptance, these models suffer from several fundamental limitations, including lumped descriptions of cellular metabolism and the assumption of cellular homogeneity. In addition to extending the applicability of existing methods, future research and development efforts are expected to focus for bioreactor optimization and control
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Process control is expected to play an increasingly important role in the biotechnology industry. The development of feedback control systems that exploit advances in online measurement technology to achieve optimal productivity of continuous and fed-batch bioreactors is one of the most important challenges in biochemical manufacturing. This article provides an overview of current and emerging bioreactor control strategies based on unstructured dynamic models of cell growth and product formation. Despite their widespread acceptance, these models suffer from several fundamental limitations, including lumped descriptions of cellular metabolism and the assumption of cellular homogeneity. In addition to extending the applicability of existing methods, future research and development efforts are expected to focus for bioreactor optimization and control
Key concepts: Biochemical engineering, Bioreactor, Exploit, Cellular metabolism, Computer science, Process control, Process (computing), Advanced process control