On‐Line Analysis of Broth

Schügerl, K.

doi:10.1002/9783527620852.ch5

Cited by 14 publications

(3 citation statements)

References 75 publications

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“…Bioprocess‐control strategy development requires a large number of time‐consuming and expensive experiments. Adequate mathematical models describing the biological‐process characteristics assist the development of appropriate process protocols and control strategies and may contribute to decreasing the experimental effort , . Process models are also used within operator training simulators (OTS), which describe the pertinent chemical‐, physical‐, and biological‐process phenomena and their interactions , .…”

Section: Introductionmentioning

confidence: 99%

Modeling Suspension Cultures of Microbial and Mammalian Cells with an Adaptable Six‐Compartment Model

et al. 2017

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Process models can be used for model‐based control strategies, but model development is a time‐consuming and laborious task. To reduce the modeling effort, a new structured compartment model was developed, which may easily be adapted to different cultivation processes. The proposed six‐compartment model was used to describe the time courses of cultivations of bacteria, yeast, fungi, and mammalian cell lines, namely, Escherichia coli, Lactobacillus delbrueckii, Saccharomyces cerevisiae, Cyathus striatus, and a hybridoma mammalian cell line. The model can describe the time courses of important state variables and can be adapted to the cultivation processes by parameterization. This reduces the modeling effort for a new process significantly.

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Section: Introductionmentioning

confidence: 99%

Modeling Suspension Cultures of Microbial and Mammalian Cells with an Adaptable Six‐Compartment Model

et al. 2017

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“…Batch process optimization and scheduling have received great attention in the chemical, food, and pharmaceutical industries, motivated by the increasing pressure to improve process efficiency with reduced operation costs . Pinto et al overviewed the assignment and sequencing for process scheduling with the mathematical programming methods.…”

Section: Introductionmentioning

confidence: 99%

Online Application‐Oriented Optimal Scheduling for 2‐keto‐l‐gulonic Acid Production

Cui

et al. 2015

Can J Chem Eng

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An optimal scheduling approach for the 2‐keto‐L‐gulonic acid (2‐KGA) fermentation process is proposed to improve allocation of L‐sorbose resources with the aim of profit maximization in a multi‐bioreactor workshop. The empirical operation in 2‐KGA cultivation under study is to assign the same quantity of L‐sorbose to each batch without taking batch‐to‐batch variations into account, while the optimal scheduling approach presented in this paper will determine L‐sorbose feeding according to the evaluation of the profit‐making ability of the individual batch. Each 2‐KGA batch is classified online according to the prediction of the profit function, so that each batch is assigned into different profit‐making categories. Pseudo‐online scheduling is implemented with the data of industrial 2‐KGA cultivations. A total profit increase of 6–7 % is found to be achievable for the workshop in comparison with the empirical operation.

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“…To solve the earlier issue, soft sensor techniques become appealing, among which Bayesian methods are reported and provide a rigorous general framework for the state estimation in fermentation process . Bayesian methods construct the posterior density distribution (PDF) of state on the basis of all available information by iterative prediction and updating steps.…”

Section: Introductionmentioning

confidence: 99%

On‐line estimation of glucose and biomass concentration in batch fermentation process using particle filter with constraint

Zhao

Shao

Huang

et al. 2012

Asia-Pacific J Chem Eng

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In most of fermentation processes, the substrate and biomass concentrations greatly influence the yield of the targeted product. In this paper, considering the nonlinear and non-Gaussian nature of the fermentation processes, the particle filter method is introduced to estimate the substrate and biomass states, and an algorithm integrating optimization strategy with resampling is proposed to deal with constraints on states. The proposed approach investigates the constraint directly on the estimated value rather than on particles. If the estimation violates constraints, the optimal estimation is firstly obtained by the optimization approach, and then, the resampling and optimization strategy are iteratively used to randomly draw a particle each time among the violated posterior particles and project it onto the feasible region. The resampling and optimization steps are iterated until the state estimation, derived from posterior particles, reaches better performance than that through previous optimization formulation or all the violated posterior particles have been projected onto the feasible region. Compared with the other previous optimization approaches, the proposed method results in a better balance between reducing the on-line computation load and obtaining more effective posterior particles.

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On‐Line Analysis of Broth

Cited by 14 publications

References 75 publications

Modeling Suspension Cultures of Microbial and Mammalian Cells with an Adaptable Six‐Compartment Model

Modeling Suspension Cultures of Microbial and Mammalian Cells with an Adaptable Six‐Compartment Model

Online Application‐Oriented Optimal Scheduling for 2‐keto‐l‐gulonic Acid Production

On‐line estimation of glucose and biomass concentration in batch fermentation process using particle filter with constraint

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