Model-driven design and validation of glucose supply control in a tubular photobioreactor operated under oxygen-balanced mixotrophy

• Mixotrophy in a tubular photobioreactor was mimicked by the tank-in-series approach. • The investigation of the retention time distribution led to a tank number of 100. • Different PID configurations were compared for oxygen stability with constant light. • The chosen controller kept stable oxygen levels also under outdoor light conditions. • Scale-down validation proved oxygen predictions but showed faster dynamics in vivo . Scaling up bioprocesses remains challenging due to the partially unpredictable and suboptimal behavior of microbes during scale transition. Mathematical modelling serves as a valuable tool in navigating these challenges. In this study, we developed and validated a kinetic model based on the tank-in-series approach for a novel bioprocess known as oxygen-balanced mixotrophy with the microalga Galdieria sulphuraria . This model aims to facilitate the design of an effective glucose feeding control strategy tailored for two-phase tubular photobioreactors ( TPBRs ). The residence time distribution of our reference reactor was investigated by means of a tracer experiment. Qualitative analysis of the results indicated that our system was optimally represented by simulations with a 100 stirred-tank reactors ( STRs ). The controlled variable, oxygen concentration in the gas phase, showed a downward trend in simulations with simplified conditions: fixed oxygen production and balanced glucose supply. The decrease was caused by dominant net heterotrophic activity and accumulation of CO 2 in the gas phase. Different configurations of a proportional-integral-derivative ( PID ) controller were designed by means of the ultimate gain method and compared under these simplified conditions. The most effective PID controller was implemented and refined in simulations with outdoor weather conditions. The model was validated successfully by simulating over time in a lab-scale STR the spatial fluctuations happening in a TPBR . The empirical oxygen consumption and production were faster and steeper than in the model, probably due to inaccuracies in parameter estimation or biomass adaptation.