LAPSE:2023.9573
Published Article

LAPSE:2023.9573
Model Based Optimal Control of the Photosynthetic Growth of Microalgae in a Batch Photobioreactor
February 27, 2023
Abstract
The present paper investigates the optimal control of the photosynthetic growth process in an artificial light photobioreactor operated in batch mode, the objective being to find an optimal incident light intensity for which the consumption of light energy, for any amount of newly formed biomass, is minimal. By using a simple and reliable model for the photosynthetic growth of microalgae of microalgae, predictions can be made on the quantity of produced biomass and on the amount of light consumed, whose ratio gives the biomass yield on light energy. This variable is unimodal on the allowed range of incident light intensities and has been used as objective function. An improved objective function is proposed by using the specific growth rate and a weighing factor that allows obtaining the desired amount of biomass while the light energy consumption is optimal. A closed-loop control structure has been designed based on the developed optimization algorithm. The optimal controller has been validated in simulation, comparing different lengths of the optimization horizon and the sampling period. It was found that a bigger sampling period, for the cases where there is no online information on the biomass concentration, does not significantly affect the productivity. The optimization algorithm can be used either online or offline, being useful for various experimental setups.
The present paper investigates the optimal control of the photosynthetic growth process in an artificial light photobioreactor operated in batch mode, the objective being to find an optimal incident light intensity for which the consumption of light energy, for any amount of newly formed biomass, is minimal. By using a simple and reliable model for the photosynthetic growth of microalgae of microalgae, predictions can be made on the quantity of produced biomass and on the amount of light consumed, whose ratio gives the biomass yield on light energy. This variable is unimodal on the allowed range of incident light intensities and has been used as objective function. An improved objective function is proposed by using the specific growth rate and a weighing factor that allows obtaining the desired amount of biomass while the light energy consumption is optimal. A closed-loop control structure has been designed based on the developed optimization algorithm. The optimal controller has been validated in simulation, comparing different lengths of the optimization horizon and the sampling period. It was found that a bigger sampling period, for the cases where there is no online information on the biomass concentration, does not significantly affect the productivity. The optimization algorithm can be used either online or offline, being useful for various experimental setups.
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Keywords
biomass yield on light energy, lumostatic batch, microalgae, optimal control, photobioreactor
Subject
Suggested Citation
Ifrim GA, Titica M, Horincar G, Antache A, Baicu L, Barbu M, Guzmán JL. Model Based Optimal Control of the Photosynthetic Growth of Microalgae in a Batch Photobioreactor. (2023). LAPSE:2023.9573
Author Affiliations
Ifrim GA: Faculty of Automation, Computers, Electrical and Electronic Engineering, Dunarea de Jos University, Domneasca 47, 800008 Galati, Romania [ORCID]
Titica M: Nantes Université, CNRS, Oniris, GEPEA, UMR 6144, F-44600 Saint-Nazaire, France
Horincar G: Faculty of Food Science and Engineering, Dunarea de Jos University, Domneasca 47, 800008 Galati, Romania
Antache A: Faculty of Food Science and Engineering, Dunarea de Jos University, Domneasca 47, 800008 Galati, Romania
Baicu L: Faculty of Automation, Computers, Electrical and Electronic Engineering, Dunarea de Jos University, Domneasca 47, 800008 Galati, Romania
Barbu M: Faculty of Automation, Computers, Electrical and Electronic Engineering, Dunarea de Jos University, Domneasca 47, 800008 Galati, Romania [ORCID]
Guzmán JL: Department of Informatics, University of Almería, CIESOL-ceiA3, 04120 Almería, Spain [ORCID]
Titica M: Nantes Université, CNRS, Oniris, GEPEA, UMR 6144, F-44600 Saint-Nazaire, France
Horincar G: Faculty of Food Science and Engineering, Dunarea de Jos University, Domneasca 47, 800008 Galati, Romania
Antache A: Faculty of Food Science and Engineering, Dunarea de Jos University, Domneasca 47, 800008 Galati, Romania
Baicu L: Faculty of Automation, Computers, Electrical and Electronic Engineering, Dunarea de Jos University, Domneasca 47, 800008 Galati, Romania
Barbu M: Faculty of Automation, Computers, Electrical and Electronic Engineering, Dunarea de Jos University, Domneasca 47, 800008 Galati, Romania [ORCID]
Guzmán JL: Department of Informatics, University of Almería, CIESOL-ceiA3, 04120 Almería, Spain [ORCID]
Journal Name
Energies
Volume
15
Issue
18
First Page
6535
Year
2022
Publication Date
2022-09-07
ISSN
1996-1073
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Original Submission
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PII: en15186535, Publication Type: Journal Article
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LAPSE:2023.9573
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https://doi.org/10.3390/en15186535
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Feb 27, 2023
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