Fuzzy Logic-Based Adaptive Control of Specific Growth Rate in Fed-Batch Biotechnological Processes. A Simulation Study

Unveiling the potential of specific growth rate control in fed-batch fermentation: bridging the gap between product quantity and quality

During the epoch of sustainable development, leveraging cellular systems for production of diverse chemicals via fermentation has garnered attention. Industrial fermentation, extending beyond strain efficiency and optimal conditions, necessitates a profound understanding of microorganism growth characteristics. Specific growth rate (SGR) is designated as a key variable due to its influence on cellular physiology, product synthesis rates and end-product quality. Despite its significance, the lack of real-time measurements and robust control systems hampers SGR control strategy implementation. The narrative in this contribution delves into the challenges associated with the SGR control and presents perspectives on various control strategies, integration of soft-sensors for real-time measurement and control of SGR. The discussion highlights practical and simple SGR control schemes, suggesting their seamless integration into industrial fermenters. Recommendations provided aim to propose new algorithms accommodating mechanistic and data-driven modelling for enhanced progress in industrial fermentation in the context of sustainable bioprocessing.

Simple Gain-Scheduled Control System for Dissolved Oxygen Control in Bioreactors

An adaptive control system for the set-point control and disturbance rejection of biotechnological-process parameters is presented. The gain scheduling of PID (PI) controller parameters is based on only controller input/output signals and does not require additional measurement of process variables for controller-parameter adaptation. Realization of the proposed system does not depend on the instrumentation-level of the bioreactor and is, therefore, attractive for practical application. A simple gain-scheduling algorithm is developed, using tendency models of the controlled process. Dissolved oxygen concentration was controlled using the developed control system. The biotechnological process was simulated in fed-batch operating mode, under extreme operating conditions (the oxygen uptake-rate’s rapidly and widely varying, feeding and aeration rate disturbances). In the simulation experiments, the gain-scheduled controller demonstrated robust behavior and outperformed the compared conventional PI controller with fixed parameters.

Novel Strategy for the Calorimetry-Based Control of Fed-Batch Cultivations of Saccharomyces cerevisiae

Typical controllers for fed-batch cultivations are based on the estimation and control of the specific growth rate in real time. Biocalorimetry allows one to measure a heat signal proportional to the substrate consumed by cells. The derivative of this heat signal is usually used to evaluate the specific growth rate, introducing noise to the resulting estimate. To avoid this, this study investigated a novel controller based directly on the heat signal. Time trajectories of the heat signal setpoint were modelled for different specific growth rates, and the controller was set to follow this dynamic setpoint. The developed controller successfully followed the setpoint during aerobic cultivations of Saccharomyces cerevisiae, preventing the Crabtree effect by maintaining low glucose concentrations. With this new method, fed-batch cultivations of S. cerevisiae could be reliably controlled at specific growth rates between 0.075 h−1 and 0.20 h−1, with average root mean square errors of 15 ± 3%.