微生物培養プロセスの状態認識への知識工学的手法の応用

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The application of computing intelligence, specifically fuzzy logic and a neural network, to feature capturing, state recognition, fault diagnosis, and control in bioprocesses is discussed through three examples of Saccharomyces cerevisiae fermentations. The ethanol concentration in a fed-batch culture was controlled by a newly developed fuzzy controller that is also to diagnose the status of the glucose concentration in the medium, i. e., the depletion or overfeeding of glucose, using not only the ethanol concentration data but also the carbon dioxide concentration in the exhaust gas. As a result, the control performance was much improved and overaction of the controller was avoided. A fuzzy physiological state recognition system was developed as a powerful tool to capture the physiological states in the fed-batch fermentation process. The error vector was newly defined in the macroscopic elemental balance. The physiological states were characterized by a database of error vectors, and membership functions for state recognition were constructed based on the error vectors. The physiological states could be recognized, including an abnormal case in which aerobic ethanol production occurred with low growth. A technique for the integration of fuzzy logic and mathematical and stoichiometric analysis is also discussed. A novel neural network-an autoassociative neural network(AANN)-was applied to fault diagnosis in an α-amylase production process using a temperature-sensitive mutant of Saccharomyces cerevisiae. Faults and uncertainties, such as faulty sensors and plasmid instability, significantly affected the performance of the optimized process. The autoassociative neural network was trained so that the network inputs were reproduced at the output layer. The features of the time courses of the state variables in"good"fermentations were captured by the AANN, and the data from"bad"fermentations could be discriminated successfully. By implementing corrective action after fault detection, performance was recovered and the final production amount was increased.
社団法人日本生物工学会の論文
1998-08-25

微生物培養プロセスの状態認識への知識工学的手法の応用

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