Active disturbance rejection control: an application to continuous microalgae photobioreactors

• Published in: Journal of chemical technology and biotechnology (1986) Vol. 98; no. 12; pp. 3004 - 3015
• Main Authors: Sangregorio‐Soto, Viyils, Mazzanti, Gianfranco, Cortés‐Romero, John A., Garzón‐Castro, Claudia L.
• Format: Journal Article
• Language: English
• Published: Bognor Regis Wiley Subscription Services, Inc 01.12.2023
• Subjects: Active control; Algae; Aquatic microorganisms; Biomass; Controllers; Disturbances; Dunaliella tertiolecta; Mathematical models; Microalgae; Performance degradation; Photobioreactors; Process variables; Rejection; Robust control
• ISSN: 0268-2575; 1097-4660
• DOI: 10.1002/jctb.7506

Abstract BACKGROUND Mathematical modelling is a widely employed approach for investigating the growth behaviour of microalgae. As a result, the development of model‐based controllers to regulate process variables has garnered increasing attention. However, despite the significant efforts invested in this area, control performance can be adversely affected by unmodelled dynamics and disturbances. RESULTS Two active disturbance rejection controllers (ADRC) were designed to enable robust tracking of biomass concentration in continuous microalgae photobioreactors, with reduced reliance on the mathematical model of the system. The controllers were tuned to achieve a nonovershoot response and minimize settling time based on the culture's characteristics. Simulations were performed using optimal setpoints specific to each model. The results showcased a maximum output signal deviation of ±2.2%, ±7.8% and ± 7.62% for the Dunaliella tertiolecta , Isochrysis affinis galbana and Chlorella vulgaris models, respectively, regardless of the presence of simulated disturbances. CONCLUSIONS The findings of this study significantly contribute to the advancement of the field of sustainable microalgae production. By introducing less dependent model‐based controllers, this research enhances the feasibility of implementing robust control strategies. These controllers require only knowledge of the equation system's order and the control gain function, simplifying the design process. This approach effectively addresses control performance degradation arising from unmodelled dynamics and disturbances. The ability to maintain desired process variables through ADRC controllers not only ensures improved control performance, but also supports the cultivation of specific microalgal species, when an accurate model is not available, thus promoting the overall progress and viability of microalgae biomass production. © 2023 Society of Chemical Industry.