Model predictive control coupled with economic and environmental constraints for optimum algal production
Abstract
Algae production process is a key cost center in production of biofuels/bioproducts from microalgae. Decline in the growth of algae in outdoor ponds during non-optimal conditions is one of the hurdles for achieving consistently high algal production rates. An optimal controller can be used to overcome this limitation and provide reliable growth in outdoor conditions. A model predictive controller (MPC) was developed to optimize the algal growth, predicted by flux balance analysis, under natural disturbances, embedding within the cost function, the economic and environmental constraints associated with the process. The model, developed in MATLAB, was validated on a 30-L continuous algal culture under light, temperature and a combination of light and temperature disturbances. The MPC proved effective in minimization of a decrease in growth under these natural disturbances. The growth rates with MPC were observed to be 79-116% higher as compared to the non-MPC growth.
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Predictive model control is more stable to changes in state variables and uncertainties in the model, but has difficulties with distortions not contemplated in the model.
“Although this technique is more stable to changes in state variables and uncertainties in the model, it has difficulties with distortions not contemplated in the model.”
From A turbidity sensor development based on NL-PI observers: Experimental application to the control of a Sinaloa’s River Spirulina maxima cultivation (2020) · cites this paper as [38]
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Valuable Products from Biotechnology of Microalgae
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Self-citationCornet, J. F., Dussap, C. G., & Dubertret, G. (1992) · Biotechnology and Bioengineering · doi:10.1002/bit.260400709 · Cited by 177 · see citing works
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Doan, Y. T.-T., Ho, M.-T., Nguyen, H.-K., & Han, H.-D. (2021) · Journal of Applied Phycology · doi:10.1007/s10811-021-02488-y · Cited by 20 · see citing works
Flores, G., Rodriguez-Mata, A. E., Amabilis-Sosa, L. E., Gonzalez-Huitron, V. A., Hernández-González, O., & Lopéz-Peréz, P. A. (2020) · Open Chemistry · doi:10.1515/chem-2020-0119 · Cited by 14 · see citing works
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- Authors
- Juneja, A., & Murthy, G. S.
- Affiliations
- Oregon State University (US)
- Corresponding author
- Murthy, Ganti S.
- Venue
- Bioresource Technology
- Publisher
- Elsevier BV
- Published
- 2018-02
- Volume
- 250
- Pages
- 556-563
- ISSN
- 0960-8524 (ISSN-L)
- OpenAlex
- W2769264253
- Cited by
- 29
- References
- 3
- Citations by year
- 2026: 5 · 2025: 3 · 2024: 4 · 2023: 4 · 2022: 3 · 2021: 4 · 2020: 3 · 2019: 3
- FWCI
- 0.44
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Bioresource Technology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Algal biology and biofuel production
- Physical Sciences › Engineering › Control and Systems Engineering › Advanced Control Systems Optimization
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Keywords
- model predictive control, microalgae cultivation, flux balance analysis, economic constraints, environmental constraints, biofuel production
- MeSH terms
- Temperature, Biomass, Biofuels, Microalgae, Ponds
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