Robust adaptive control of yeast fed-batch cultures

Renard, F.; Wouwer, Alain Vande

doi:10.1016/j.compchemeng.2007.05.008

Cited by 40 publications

(8 citation statements)

References 7 publications

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“…Some researchers have also studied the effect of pulsed feeding on biomass yield using dissolved oxygen as a control parameter (Kasperski and Miskiewicz, 2008). Two different adaptive robust controllers were designed using minimal apriori knowledge and minimal measurement information to maximize biomass productivity in aerobic cultures of S. cerevisiae (Renard and Vande Wouwer, 2008). The yield calculated from our experimental results is 0.61.…”

Section: Maximization Of Biomass With High Inoculum Densitymentioning

confidence: 99%

Maximizing biomass concentration in baker’s yeast process by using a decoupled geometric controller for substrate and dissolved oxygen

Chopda

Rathore

Gomes

2015

Bioresource Technology

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Section: Maximization Of Biomass With High Inoculum Densitymentioning

confidence: 99%

Maximizing biomass concentration in baker’s yeast process by using a decoupled geometric controller for substrate and dissolved oxygen

Chopda

Rathore

Gomes

2015

Bioresource Technology

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“…So, if it is assumed in the following that oxygen is not a limiting factor and has no significant influence on bacterial growth, the dynamic model Eqs. (6) and (7) can be reduced to the consideration of:…”

Section: Process Modelingmentioning

confidence: 99%

“…Other approaches developed in the framework of yeast fed-batch cultures could also be transposed in view of the similarities in the overflow metabolism (ethanol production in yeast cultures and acetate production in bacteria cultures, when the respiratory capacity is exceeded). For instance, the robust RST strategy devised in [5,6] in principle could be applied.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Predictive Control of Fed‐Batch Cultures of Escherichia coli

Tebbani¹,

Dumur²,

Hafidi³

et al. 2010

Chem Eng & Technol

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A strategy for controlling a fed-batch Escherichia coli culture is described to maintain the culture at the boundary between oxidative and oxido-fermentative regimes. A nonlinear predictive controller is designed to regulate the acetate concentration, constraining the feed rate to follow an optimal reference profile which maximizes the biomass growth. For the sake of simplicity and efficiency, the original problem is converted into an unconstrained nonlinear programming problem, solved by control vector parameterization techniques. The robustness of the structure is further improved by explicitly including the difference between system and model prediction. A robustness study based on a Monte Carlo approach is used to evaluate the performance of the proposed controller. This control law is finally compared to the generic model control strategy.

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“…Hence, control of them is a delicate task; Nonlinearity and non-stationarity which make modeling and parameter estimation particularly difficult perturbs such processes. Moreover, the scarcity of online measurements of the component concentrations (essential substrates, biomass and products of interest) makes this task more sophisticated [3]. Hence, conventional control methods do not succeed in such task.…”

Section: Introductionmentioning

confidence: 98%

Model predictive control of a nonlinear fed-batch fermentation process

Ashoori

Ghods

Khaki‐Sedigh

et al. 2008

2008 10th International Conference on Control, Automation, Robotics and Vision

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Bioprocesses, which are involved in producing different antibiotics and other pharmaceutical products, may be conveniently classified according to the mode chosen for the process: either batch, fed-batch or continuous. From the control engineer's viewpoint it is the fed-batch processes, however, which present the greatest challenge to get a pure product with a high concentration. To achieve this goal, control of the following parameters has significant importance dealing with these processes: Temperature, pH, Dissolved oxygen (DO2). Bioprocesses have complicated dynamics. Hence, their control is a delicate task; Nonlinearity and non-stationarity, which make modeling and parameter estimation particularly difficult perturbs such processes. Moreover, the scarcity of on-line measurements of the component concentrations (essential substrates, biomass and products of interest) makes this task more sophisticated. In this paper, Model predictive control (MPC) based on a detailed unstructured model for penicillin production in a fed-batch fermentor has been developed. MPC is performed via determining the control signal by minimizing a cost function in each step. The results of this controller to maximize penicillin concentration have been displayed and also compared with the results of auto-tuned PID controller used in previous works.

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Robust adaptive control of yeast fed-batch cultures

Cited by 40 publications

References 7 publications

Maximizing biomass concentration in baker’s yeast process by using a decoupled geometric controller for substrate and dissolved oxygen

Maximizing biomass concentration in baker’s yeast process by using a decoupled geometric controller for substrate and dissolved oxygen

Nonlinear Predictive Control of Fed‐Batch Cultures of Escherichia coli

Model predictive control of a nonlinear fed-batch fermentation process

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