Optimization of microalgal photobioreactor system using model predictive control with experimental validation
Abstract
To maximize biomass and lipid concentrations, various optimization methods were investigated in microalgal photobioreactor systems under mixotrophic conditions. Lipid concentration was estimated using unscented Kalman filter (UKF) with other measurable sources and subsequently used as lipid data for performing model predictive control (MPC). In addition, the maximized biomass and lipid trajectory obtained by open-loop optimization were used as target trajectory for tracking by MPC. Simulation studies and experimental validation were performed and significant improvements in biomass and lipid productivity were achieved in the case where MPC was applied. However, occurence of a lag phase was observed while manipulating the feed flow rates, which is induced by large amount of inputs. This is an important phenomenon that can lead to model-plant mismatch and requires further study for the optimization of microalgal photobioreactors.
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In a continuation of the previous research, the same authors used only UKF to estimate total lipids through turbidity and glucose measurements and used this data to perform model predictive control (MPC).
“In a continuation of the previous research, the same authors used only UKF to estimate total lipids through turbidity and glucose measurements and used this data to perform model predictive control (MPC).”
From Software sensors in the monitoring of microalgae cultivations (2024) · cites this paper as Yoo et al. 2016
Cites
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On-line soft sensing in upstream bioprocessing
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Porras Reyes, L., Havlik, I., & Beutel, S. (2024) · Reviews in Environmental Science and Bio/Technology · doi:10.1007/s11157-023-09679-8 · Cited by 48 · see citing works
“It was pointed out that significant improvements in biomass and lipid productivity were achieved when MPC calculation was applied, however, inaccuracies as “lag phase” were observed due to the introduction of large amounts of inputs (Yoo et al. 2016).”
A hybrid approach for photobioreactor modeling in CO2 biofixation using microalgae cultivation
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- Authors
- Yoo, S. J., Jeong, D. H., Kim, J. H., & Lee, J. M.
- Affiliations
- Seoul National University (KR)
- Corresponding author
- Lee, Jong Min
- Venue
- Bioprocess and Biosystems Engineering
- Published
- 2016-04-19
- Volume
- 39
- Issue
- 8
- Pages
- 1235-1246
- ISSN
- 1615-7591 (ISSN-L)
- 1615-7605
- OpenAlex
- W2336283590
- Cited by
- 28
- References
- 4
- Citations by year
- 2026: 1 · 2025: 6 · 2024: 2 · 2023: 4 · 2022: 3 · 2021: 4 · 2020: 1 · 2019: 1 · 2018: 3 · 2017: 3
- FWCI
- 0.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Bioprocess and Biosystems Engineering (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Ministry of Trade, Industry and Energy (10038671)
- Ministry of Science, ICT , Future Planning
- 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
- microalgae, photobioreactors, model predictive control, mixotrophic cultivation, lipid production, biomass production, unscented Kalman filter, state estimation, lag phase, model mismatch, process optimization
- MeSH terms
- Models, Theoretical, Microalgae, Photobioreactors
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