Robust control of fed-batch high-cell density cultures: a simulation-based assessment: Simulation-based assessment of probing and model-based control strategies for robust operation of high-cell density cultures in fed-batch mode

被引:0
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作者
Ibáñez F. [1 ]
Saa P.A. [1 ,2 ]
Bárzaga L. [3 ]
Duarte-Mermoud M.A. [4 ]
Fernández-Fernández M. [5 ,6 ]
Agosin E. [1 ]
Pérez-Correa J.R. [1 ]
机构
[1] Departamento de Ingeniería Química y Bioprocesos, Facultad de Ingeniería, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, Casilla 306 Correo 22, Santiago
[2] Institute for Mathematical and Computational Engineering, Pontifical Catholic University of Chile, Av. Vicuña Mackenna 4860, Casilla 306 Correo 22, Santiago
[3] Departamento de Ingeniería Eléctrica, Facultad de Ciencias Físicas y Matemáticas, Universidad de Chile, Av. Tupper 2007, Casilla 412-3, Santiago
[4] Advanced Mining Technology Center, University of Chile, Av. Tupper 2007, Santiago
[5] Facultad de Ingeniería y Arquitectura, Universidad Central de Chile, Av. Santa Isabel 1186, Santiago
[6] Departamento de Ingeniería Eléctrica, Facultad de Ingeniería, Universidad de Talca, Camino a Los Niches km 1, Curicó
来源
关键词
Bioprocess development; Control strategy; Dynamic optimization; High-density cultures; Overflow metabolism;
D O I
10.1016/j.compchemeng.2021.107545
中图分类号
学科分类号
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. © 2021 Elsevier Ltd
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