模型预测控制
控制器(灌溉)
控制理论(社会学)
参数统计
启发式
自适应控制
非线性系统
噪音(视频)
计算机科学
控制(管理)
工程类
控制工程
数学
生物
统计
人工智能
图像(数学)
物理
量子力学
农学
作者
Francisco Javier Muñoz Ibáñez,Pedro A. Saa,Lisbel Bárzaga,Manuel A. Duarte‐Mermoud,Mario Fernández‐Fernández,Eduardo Agosín,José Ricardo Pérez-Correa
标识
DOI:10.1016/j.compchemeng.2021.107545
摘要
High-cell density cultures (HCDC), prone to metabolic overflow, are typically operated in fed-batch mode to maximize productivity. We developed a simulation-based procedure for assessing advanced control strategies for HCDC, aiming to avoid metabolic overflow. We tested a heuristic controller, a nonlinear model predictive controller (NMPC), and two adaptive controllers under realistic conditions. As a case study, we considered the growth of a carotenoid-producing Saccharomyces cerevisiae strain developed in our laboratory. Our control simulations were consistent with experimental results reported in the literature with equivalent control strategies. All tested controllers could cope well with measurement noise and model parameter variations, reaching low ethanol concentrations (≤ 1 g/L), albeit with substantially different biomass productivities. The NMPC algorithm yielded the best performance even under parametric uncertainty, achieving high biomass concentrations (200 gDCW/L) and cell productivities (5 gDCW/L/h). The presented systematic procedure helps in the evaluation of novel control strategies before their implementation in practice.
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