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基于神经网络的模型预测控制器对连续补料分批发酵过程的控制

Control of continuous fed-batch fermentation process using neural network based model predictive controller.

作者信息

Kiran A Uma Maheshwar, Jana Asim Kumar

机构信息

Department of Chemical Engineering, McMaster University, Hamilton, ON L8S 4L7, Canada.

出版信息

Bioprocess Biosyst Eng. 2009 Oct;32(6):801-8. doi: 10.1007/s00449-009-0306-0. Epub 2009 Mar 4.

Abstract

Cell growth and metabolite production greatly depend on the feeding of the nutrients in fed-batch fermentations. A strategy for controlling the glucose feed rate in fed-batch baker's yeast fermentation and a novel controller was studied. The difference between the specific carbon dioxide evolution rate and oxygen uptake rate (Qc - Qo) was used as controller variable. The controller evaluated was neural network based model predictive controller and optimizer. The performance of the controller was evaluated by the set point tracking. Results showed good performance of the controller.

摘要

在补料分批发酵中,细胞生长和代谢产物的产生很大程度上取决于营养物质的供给。研究了一种补料分批面包酵母发酵中控制葡萄糖进料速率的策略以及一种新型控制器。特定二氧化碳释放速率与氧气摄取速率之差(Qc - Qo)用作控制器变量。所评估的控制器是基于神经网络的模型预测控制器和优化器。通过设定值跟踪对控制器的性能进行了评估。结果表明该控制器具有良好的性能。

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