Model-Free Control approach for pH Regulation in Thin-Layer Photobioreactors

Abstract

Thin-layer photobioreactors (TLRs) exhibit fast hydrodynamic and thermal dynamics, strong nonlinear photosynthetic responses and significant time-variability due to irradiance fluctuations and biomass growth. These characteristics challenge conventional model-based control strategies, whose tuning degrades under rapidly changing operating conditions. This work presents the experimental implementation of a model-free control approach, Extremum Seeking Control (ESC), for performance optimization in a semi-industrial thin-layer photobioreactor. Unlike previous studies in raceway ponds, the reduced hydraulic inertia of TLR systems enables the adaptation of this control strategy to accelerate convergence while preserving gradient estimation accuracy. The proposed approach is experimentally compared against classical on-off control and ESC configurations with and without feedforward compensation of solar irradiance. Beyond control performance metrics, biological indicators such as biomass concentration and productivity are evaluated to assess the impact on process efficiency. Results show that the proposed ESC strategy reduced cumulative CO$_2$ consumption by approximately 39 % and decreased the accumulated pH tracking error by more than 60 % compared with conventional on-off control, while biomass- and irradiance-normalised indicators confirmed a more efficient use of injected carbon. These results demonstrate that high-frequency ESC can improve regulation performance and carbon utilisation efficiency in fast photobioreactor systems, highlighting its suitability for thin-layer cultivation under outdoor conditions.