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首页> 外文期刊>Bioprocess and Biosystems Engineering >A soft sensor based on online biomass measurements for the glucose estimation and control of fed-batch cultures of Bacillus thuringiensis
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A soft sensor based on online biomass measurements for the glucose estimation and control of fed-batch cultures of Bacillus thuringiensis

机译：基于在线生物量测量的软传感器，用于苏云金芽孢杆菌补料分批培养的葡萄糖估算和控制

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摘要

On bioprocess engineering, experimental measurements are always a costly part of the modeling effort; therefore, there is a constant need to develop cheaper, simpler, and more efficient methodologies to exploit the information available. The aim of the present work was to develop a soft sensor with the capacity to perform reliable substrate predictions and control in microbial cultures of the fed-batch type, using mainly microbial growth data. This objective was achieved using dielectric spectroscopy technology for online monitoring of microbial growth and hybrid neural networks for online prediction of substrate concentration. The glucose estimator was integrated to a fuzzy logic controller to control the substrate concentration in a fed-batch experiment. Dielectric spectroscopy is a technology sensitive to the air volume fraction in the culture media and the turbulence generated by the agitation; however, the introduction of a polynomial function for the calibration of the permittivity signal allowed biomass estimations with an approximation error of 2%. The methodology presented in this work was successfully implemented for the glucose prediction and control of a fed-batch culture of Bacillus thuringiensis with an approximation error of 6%.
机译：在生物过程工程中，实验测量始终是建模工作中昂贵的一部分。因此，始终需要开发更便宜，更简单，更有效的方法来利用可用信息。本工作的目的是开发一种软​​传感器，其能力主要使用微生物生长数据在补料分批类型的微生物培养物中进行可靠的底物预测和控制。使用介电光谱技术在线监测微生物生长，使用混合神经网络在线预测底物浓度可以实现该目标。葡萄糖估算器集成到模糊逻辑控制器中，以在补料分批实验中控制底物浓度。介电谱技术对培养基中的空气体积分数和搅拌产生的湍流敏感。然而，引入用于校准介电常数信号的多项式函数使得生物量估计的近似误差为2％。这项工作中介绍的方法已成功地用于苏云金芽孢杆菌补料分批培养的葡萄糖预测和控制，其近似误差为6％。

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