Nonlinear control strategies for a micro-aerobic, fermentation process

In this paper, we propose a new strategy to control the yield and productivity of the fermentation process by viewing the fermentation process as a multi-scale process, where the mixing conditions in terms of aeration rate and stirrer speed are considered in studying the bioreactor dynamics. The inc...

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Main Authors: Liew, Emily, Samyudia, Yudi
Format: Book Chapter
Published: Elsevier 2012
Online Access:http://hdl.handle.net/20.500.11937/41845
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author Liew, Emily
Samyudia, Yudi
author_facet Liew, Emily
Samyudia, Yudi
author_sort Liew, Emily
building Curtin Institutional Repository
collection Online Access
description In this paper, we propose a new strategy to control the yield and productivity of the fermentation process by viewing the fermentation process as a multi-scale process, where the mixing conditions in terms of aeration rate and stirrer speed are considered in studying the bioreactor dynamics. The inclusion of mixing for bioreactor control would allow us to influence the metabolic activities of microorganisms through the distribution of nutrients to the microbial cells. The engagement of both mixing and biological processes, however, would lead to a very complex dynamics of the bioreactor. As a result, the control strategy with a direct use of a nonlinear model will be implemented. Two different modeling techniques to capture the mixing dynamics, namely data-based and kinetics hybrid modeling are proposed. The validated nonlinear models are used in determining the optimal aeration rate and stirrer speed to maintain the desired productivity and yield of the fermentation process for different disturbance scenarios via extensive simulation studies.
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institution Curtin University Malaysia
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publishDate 2012
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spelling curtin-20.500.11937-418452017-09-13T16:00:28Z Nonlinear control strategies for a micro-aerobic, fermentation process Liew, Emily Samyudia, Yudi In this paper, we propose a new strategy to control the yield and productivity of the fermentation process by viewing the fermentation process as a multi-scale process, where the mixing conditions in terms of aeration rate and stirrer speed are considered in studying the bioreactor dynamics. The inclusion of mixing for bioreactor control would allow us to influence the metabolic activities of microorganisms through the distribution of nutrients to the microbial cells. The engagement of both mixing and biological processes, however, would lead to a very complex dynamics of the bioreactor. As a result, the control strategy with a direct use of a nonlinear model will be implemented. Two different modeling techniques to capture the mixing dynamics, namely data-based and kinetics hybrid modeling are proposed. The validated nonlinear models are used in determining the optimal aeration rate and stirrer speed to maintain the desired productivity and yield of the fermentation process for different disturbance scenarios via extensive simulation studies. 2012 Book Chapter http://hdl.handle.net/20.500.11937/41845 10.1016/B978-0-444-59507-2.50058-5 Elsevier restricted
spellingShingle Liew, Emily
Samyudia, Yudi
Nonlinear control strategies for a micro-aerobic, fermentation process
title Nonlinear control strategies for a micro-aerobic, fermentation process
title_full Nonlinear control strategies for a micro-aerobic, fermentation process
title_fullStr Nonlinear control strategies for a micro-aerobic, fermentation process
title_full_unstemmed Nonlinear control strategies for a micro-aerobic, fermentation process
title_short Nonlinear control strategies for a micro-aerobic, fermentation process
title_sort nonlinear control strategies for a micro-aerobic, fermentation process
url http://hdl.handle.net/20.500.11937/41845