Virtual Reference Feedback Tuning for Microalgae Culture Control

Descripción

Microalgae are photosynthetic microorganisms capable of fix carbon dioxide (CO2) to produce oxygen (O2) and various metabolite types. The crop of these microorganisms represents a challenge when controlling this type of bioprocess-es. The above is due to the biological, physical, and chemical variability of the ini-tial operating conditions and the non-linear dynamics of this bioprocess. To this date, different control strategies focused on the regulation of physicochemical variables such as temperature, pH, dilution rate, and light intensity, among others, have been reported. However, these control paradigms usually depend heavily on the mathematical model used to represent some multifactorial phenomena specific to the bioprocess. Or, on the contrary, parametric identification models that gen-eralize such behaviors without being able to consider all the intrinsic and extrinsic dynamics of the bioprocess. As a result, the design of model-based controllers that, to front parameter variation and disturbances, may perform less robustly. Model-Free Control strategies such as Virtual Reference Feedback Tuning (VRFT) represent a novel alternative paradigm based on virtual iterative reference generation until a system steady-state error of close to zero is achieved. The im-plementation of VRFT strategy involves: 1) collection of experimental data ob-tained from the open-loop plant to obtain the parameter values, 2) minimization of an objective function obtained from the closed-loop system, and 3) linearization of the phenomenological model of the process in its stable equilibrium region. This strategy is a tool for the robust control of bioprocesses, due to its iterative characteristic that leads to an auto-tuning (on-line/off-line) of the controller. This paper shows the design and implementation of the control strategy by the VRFT for a closed continuous microalgae culture in three flat PBRs with a volume of 3L. The control strategy was developed in Python 3.9 and Matlab 2020® and implemented on an ARM Cortex-M3 microcontroller integrated with an embed-ded system. The process variables controlled were temperature and light intensity. The results showed a follow-up to the reference values, on the one hand, a steady state temperature of 25 °C ± 0.625 °C, on the other hand, a light intensity of 100 µmol·m−2·s−1 ± 5 µmol·m−2·s−1. All this suggests that this strategy is a good al-ternative to applied in the control of bioprocesses due to the characteristics of these. In the future, it is expected that this prototype can be scale-up and taken to an industrial level to provide support for increased culture production in less time.

Período	2 dic. 2025 → 4 dic. 2025
Título del evento	4th International Conference on Smart Technologies, Systems and Applications
Tipo de evento	Conferencia
Número de la conferencia	4
Ubicación	Quito, EcuadorMostrar en mapa
Grado de reconocimiento	Internacional