Nonlinear model predictive control of fed-batch fermentations using dynamic flux balance models
Nonlinear model predictive control of fed-batch fermentations using dynamic flux balance models
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DOI：
10.1016/j.jprocont.2016.04.012
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发表时间：
2016-06-01
影响因子：
4.2
通讯作者：
Henson, Michael A.
中科院分区：
文献类型：
--
作者：
Chang, Liang;Liu, Xinggao;Henson, Michael A.
补料分批发酵是生化工业中一项重要的生产技术。以间歇进料发酵为例，提出了一种用动态通量平衡模型描述的间歇进料生物反应器非线性模型预测控制的通用方法。控制目标是通过调节葡萄糖投料速率和好氧-厌氧切换时间，在固定的末批时间下使乙醇产量最大化。通过比较NMPC和开环最优控制器的相对性能，评价了闭环实现的有效性。与开环操作策略相比，NMPC能够通过增加乙醇产量8.0%至14.7%来补偿细胞内模型的结构误差和底物摄取动力学和细胞能量学的参数误差。当生物量、葡萄糖、乙醇浓度和液体体积测量值被高斯白噪声破坏时，NMPC性能的退化最小。与基于更简单的非结构化模型的相同NMPC配方相比，基于动态通量平衡模型的NMPC可提高乙醇产量。据我们所知，这项研究首次尝试在基于非线性模型的控制方案中使用动态通量平衡模型。(C) 2016 Elsevier Ltd.版权所有。
Fed-batch fermentation is an important production technology in the biochemical industry. Using fed-batch Saccharomyces cerevisiae fermentation as a prototypical example, we developed a general methodology for nonlinear model predictive control of fed-batch bioreactors described by dynamic flux balance models. The control objective was to maximize ethanol production at a fixed final batch time by adjusting the glucose feeding rate and the aerobic-anaerobic switching time. Effectiveness of the closed-loop implementation was evaluated by comparing the relative performance of NMPC and the open-loop optimal controller. NMPC was able to compensate for structural errors in the intracellular model and parametric errors in the substrate uptake kinetics and cellular energetics by increasing ethanol production between 8.0% and 14.7% compared with the open-loop operating policy. Minimal degradation in NMPC performance was observed when the biomass, glucose, and ethanol concentration and liquid volume measurements were corrupted with Gaussian white noise. NMPC based on the dynamic flux balance model was shown to improve ethanol production compared to the same NMPC formulation based on a simpler unstructured model. To our knowledge, this study represents the first attempt to utilize a dynamic flux balance model within a nonlinear model-based control scheme. (C) 2016 Elsevier Ltd. All rights reserved.