Optimization of microalgal photobioreactor system using model predictive control with experimental validation.
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.
Institute of Chemical Processes, School of Chemical and Biological Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, Republic of Korea.
Sung Jin
SJ
Yoo
Institute of Chemical Processes, School of Chemical and Biological Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, Republic of Korea.
Dong Hwi
DH
Jeong
Institute of Chemical Processes, School of Chemical and Biological Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, Republic of Korea.
Jung Hun
JH
Kim
Institute of Chemical Processes, School of Chemical and Biological Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, Republic of Korea. jongmin@snu.ac.kr.
Jong Min
JM
Lee
D058086:Microalgae / Q000254:growth & development / Q000378:metabolism*; D008962:Models, Theoretical; D058433:Photobioreactors
Lag phase; Microalgae; Model predictive control; Photobioreactor; Unscented Kalman filter