Operability and biomimetic control of a micro-aerated fermentation process

• Published in: Computers & chemical engineering Vol. 155; p. 107511
• Main Authors: Mesquita, Thiago J.B., Campani, Gilson, Giordano, Roberto C., Ribeiro, Marcelo P.A., Horta, Antonio C.L., Zangirolami, Teresa C., Lima, Fernando V.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2021
• Subjects: Alcoholic fermentation; Biomimetic process control; Metabolic Fluxes; Micro-aeration; Operability mapping; Micro-aeration; Biomimetic process control; Operability mapping; Alcoholic fermentation; Metabolic Fluxes
• ISSN: 0098-1354; 1873-4375
• DOI: 10.1016/j.compchemeng.2021.107511

•Novel approach proposed defines operating conditions for gas-phase bioreactors.•Developed first-principles model successfully represents the main states.•Proposed framework produces a structure to control the yeast metabolism.•Contribution enables advances in bioprocess monitoring and control. The design of reliable control systems to maintain feasible optimal conditions and intensify bioprocesses is a requirement to achieve high product yields and cost-efficient process operations. Micro-aeration is an approach to increase bioprocess product yield. However, standard control strategies may present unsatisfactory performance under oxygen supply constraints. In this paper, a novel framework using process operability and biomimetic control algorithms is proposed to define a control strategy for improved micro-aerated batch process fermentations. In particular, process operability is employed to characterize the ideal operating regions. Then, the Biologically-Inspired Optimal Control Strategy (BIOCS) is implemented to take the process to the optimal path by manipulating the inlet gas flow rate and controlling the metabolic cell state. By employing the developed framework, an optimal operating region is successfully obtained for the controller to maintain the desired metabolic state. Specific scenarios of measurement noise, plant-model mismatch, and step disturbance rejection are successfully addressed in the BIO-CS implementations, while a proportional-integral controller presented noisy control actions under the same conditions. This developed control framework is a novel step towards Industry 4.0 concepts associated with bioprocess systems engineering and could also be implemented to improve other oxygen-limited processes.