Adaptive control of specific growth rate based on proton production in anaerobic fed-batch culture

1993 ◽  
Vol 15 (5) ◽  
pp. 511-516 ◽  
Author(s):  
J. I. Won ◽  
Y. L. Yang ◽  
B. G. Kim ◽  
C. Y. Choi
Keyword(s):  
Growth Rate ◽  
Adaptive Control ◽  
Specific Growth Rate ◽  
Batch Culture ◽  
Specific Growth ◽  
Fed Batch ◽  
Proton Production ◽  
Fed Batch Culture

Automated fed-batch culture of Kluyveromyces fragilis based on a novel method for on-line estimation of cell specific growth rate

2001 ◽  
Vol 9 (3) ◽  
pp. 221-231 ◽  
Author(s):  
Zairossani M. Nor ◽  
Melih I. Tamer ◽  
Jeno M. Scharer ◽  
Murray Moo-Young ◽  
Eric J. Jervis
Keyword(s):  
Growth Rate ◽  
Specific Growth Rate ◽  
Batch Culture ◽  
Specific Growth ◽  
Fed Batch ◽  
Kluyveromyces Fragilis ◽  
On Line ◽  
Novel Method ◽  
Fed Batch Culture

Optimal production of glutathione by controlling the specific growth rate of yeast in fed-batch culture

1991 ◽  
Vol 38 (2) ◽  
pp. 196-205 ◽  
Author(s):  
Hiroshi Shimizu ◽  
Katshuiro Araki ◽  
Suteaki Shioya ◽  
Ken-ichi Suga
Keyword(s):  
Growth Rate ◽  
Specific Growth Rate ◽  
Batch Culture ◽  
Specific Growth ◽  
Fed Batch ◽  
Optimal Production ◽  
Fed Batch Culture

scholarly journals Modelling, Optimization and Realization of Fed-Batch Culture using the Specific Growth Rate.

1991 ◽  
Vol 17 (3) ◽  
pp. 572-578
Author(s):  
Suteaki Shioya ◽  
Hiroshi Shimizu ◽  
Patoomporn Chim-anage ◽  
Ken-ichi Suga
Keyword(s):  
Growth Rate ◽  
Specific Growth Rate ◽  
Batch Culture ◽  
Specific Growth ◽  
Fed Batch ◽  
Fed Batch Culture

scholarly journals Fuzzy Logic-Based Adaptive Control of Specific Growth Rate in Fed-Batch Biotechnological Processes. A Simulation Study

2020 ◽  
Vol 10 (19) ◽  
pp. 6818
Author(s):  
Mantas Butkus ◽  
Jolanta Repšytė ◽  
Vytautas Galvanauskas
Keyword(s):  
Growth Rate ◽  
Fuzzy Logic ◽  
Adaptive Control ◽  
Specific Growth Rate ◽  
Control Algorithm ◽  
Specific Growth ◽  
Expert Knowledge ◽  
Fed Batch ◽  
Biotechnological Process ◽  
Model Free

This article presents the development and application of a distinct adaptive control algorithm that is based on fuzzy logic and was used to control the specific growth rate (SGR) in a fed-batch biotechnological process. The developed control algorithm was compared with two adaptive control systems that were based on a model-free adaptive technique and gain scheduling technique. A typical mathematical model of recombinant Escherichia coli fed-batch cultivation process was selected to evaluate the performance of the fuzzy-based control algorithm. The investigated control techniques performed similarly when considering the whole process duration. The adaptive PI controller with fuzzy-based parameter adaptation demonstrated advantages over the previously mentioned algorithms—especially when compensating the deviations of the SGR. These deviations usually occur when the equipment malfunctions or process disturbances take place. The fuzzy-based control system was stable within the investigated ranges. It was determined that, regarding control quality, the investigated control algorithms are suited to control the SGR in a fed-batch biotechnological process. However, substrate feeding rate manipulation and limitation needs to be used. Taking into account the time needed to design and tune the controller, the developed controller is suitable for practical applications when expert knowledge is available. The proposed algorithm can be further adapted and developed to control the SGR in other cell cultivations while running the process under substrate limitation conditions.

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