Robust multivariable control for enhanced microalgae biomass and lipid productivity in continuous photobioreactors (Robust multivariable control in continuous microalgae photobioreactors)

BACKGROUND Microalgae have high potential as a primary source (lipids and carbohydrates) for sustainable energy production ( e.g. biodiesel, biogas, bioethanol) and high‐value biomass secondary products (feed and nutrient supplements). High production costs are the main barrier to commercializing microalgal‐derived biofuels. Thus, various methods have been proposed to enhance microalgal biomass and lipid content. This paper addresses enhancements in lipid and biomass productivity in microalgal continuous photobioreactors using nonlinear programming optimization and two robust control approaches. RESULTS The favorable selection of the dilution rate and the input nutrient concentration as manipulable variables, along with the design of controllers using robust nonlinear model predictive control and modeling error compensation approaches, leads to reliable and efficient multivariable control approaches aimed at improving biomass and lipid productivities in microalgae photobioreactors simultaneously. Numerical simulations of the proposed control approaches demonstrate good and robust closed‐loop performance under significant model uncertainties and external perturbations. CONCLUSIONS Two robust controllers with simple design and structure are introduced to address underlying uncertainties in the mathematical models of microalgae photobioreactors. The proposed control schemes enable simultaneous manipulation of the dilution rate and substrate input concentration to enhance lipid and biomass productivities.