arXiv subjects

José González-Hernández

Publications and source records attributed to José González-Hernández.

3 recordsLinked to original sources

arXiv2026

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

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.

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arXiv2026

Sensor-Based Turbidostat Operation Enables Biomass Setpoint Regulation and Productivity Improvement in semi-industrial Microalgae Raceway Pond

This work presents the experimental validation of a turbidostat strategy for biomass control in a semi-industrial outdoor raceway reactor. The proposed approach regulates biomass concentration by automatically triggering dilution when the online biomass estimate exceeds a predefined threshold. To ensure safe outdoor operation, dilution was restricted to daylight periods, avoiding biomass removal under low-radiation conditions. The strategy was implemented through an industrial control architecture using an optical monitoring system for online biomass estimation. Experiments were conducted over 14 consecutive days in an 80 m$^2$ (12000 L) raceway reactor. A second parallel reactor operated in chemostat mode, with a nominal dilution of 20 % of the total volume during operating days, provided contextual information under the same outdoor conditions. The analysis focuses on the ability of the sensor-based strategy to configure and maintain the desired biomass concentration, rather than on a direct reactor-to-reactor performance ranking. During the campaign, the biomass threshold in the turbidostat reactor was changed from 1.0 to 0.8 g L$^{-1}$, demonstrating the flexibility enabled by online biomass monitoring. Excluding initial adjustment and transition days, harvested areal productivity increased from 9.52 to 23.20 g m$^{-2}$ d$^{-1}$ after reducing the operating threshold. The overall biomass balance also showed higher net areal productivity in the turbidostat reactor, reaching 20.34 g m$^{-2}$ d$^{-1}$ compared with 11.16 g m$^{-2}$ d$^{-1}$ in the parallel chemostat reactor. These results demonstrate the feasibility of robust turbidostat-based biomass control in large-scale outdoor raceway photobioreactors.

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arXiv2025

A Comprehensive Benchmark Platform for Process Control Research of Outdoor Microalgae Raceway Reactors

This paper presents a benchmarking framework to evaluate process control strategies in outdoor microalgae raceway reactors, integrating four key control regulation tasks: pH, dissolved oxygen (DO), culture volume through coordinated harvest-dilution actions, and temperature via a sump-mounted spiral heat exchanger. The benchmark is built upon a high-fidelity, experimentally calibrated dynamic model that captures the strongly coupled thermal, physicochemical, and biological processes governing industrial-scale open raceway ponds. A closed-loop simulation environment is provided, featuring realistic actuator constraints, gas transport delays, stiff integration, and a fully specified scenario based on multi-day outdoor disturbances (irradiance, temperature, wind, and humidity). Four user-replaceable controllers define the manipulation of CO2 injection, air bubbling, harvest/dilution sequencing, and heat-exchanger operation. The platform computes a unified global performance index, in addition to individual metrics for each control problem, combining tracking error, gas and energy usage, and biomass productivity, enabling consistent and quantitative comparison of alternative control strategies. Baseline regulatory architectures (On/Off, PI/PID, and Economic Model Predictive Control (EMPC)) are included to illustrate the benchmark use for classical and advanced control methods. By providing an openly specified, reproducible, and computationally tractable benchmark with well-defined function interfaces, this work aims to bridge control methodology and outdoor algal bioprocess engineering, and to support the development of multivariable control strategies for disturbance-rich environmental systems.

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