CO2 Biofixation by Microalgae

Sihem Tebbani is Associate Professor in the Automatic Control department at SUPELEC in Gif-sur-Yvette, France. Her research interests include modeling, estimation, optimization and control of bioprocesses, and more particularly of microalgae and bacteria cultures. Filipa Lopes is Associate Professor at LGPM, Ecole Centrale Paris, France. Her research interests are in the field of biological engineering with a focus on biofilms (biofouling, disinfection, dispersion, modeling) and bioprocess development (bacteria, microalgae) for wastewater treatment, high-value products and bio-energy production. Rayen Filali has a PhD in Automatic Control obtained at SUPELEC in Gif-sur-Yvette, France. His PhD thesis, in the framework of a collaboration between SUPELEC and Ecole Centrale Paris, deals with the estimation and the robust control laws of microalgae cultures for the optimization of CO2 biological consumption. Didier Dumur is Professor in the Automatic Control department at SUPELEC in Gif-sur-Yvette, France. His research interests cover theoretical and methodological aspects related to predictive control strategies and their application in multiple domains (robotics, bioprocesses, temperature control of buildings, etc.). Dominique Pareau is Professor at LGPM and Director of the White Biotechnologies Chair of the Ecole Centrale Paris, France. Her research concerns chemical engineering and biotechnologies, from the understanding of microscopic phenomena to process design, by coupling modeling and experimentation, with applications in the fields of agroresources, microalgae, waste and effluent treatments.

• Introduction ixChapter 1 Microalgae 11.1 Definition 11.2 Characteristics 21.3 Uses of microalgae 31.4 Microalgae cultivation systems 101.5 Factors affecting algae cultivation 141.6 Conclusion 21Chapter 2 CO2 Biofixation 232.1 Selection of microalgae species 252.2 Optimization of the photobioreactor design 312.3 Conclusion 32Chapter 3 Bioprocess Modeling 333.1 Operating modes 333.2 Growth rate modeling 373.3 Mass balance models 473.4 Model parameter identification 493.5 Example: Chlorella vulgaris culture 513.6 Conclusion 63Chapter 4 Estimation of Biomass Concentration 654.1 Generalities on estimation 654.2 State of the art 684.3 Kalman filter 724.4 Asymptotic observer 804.5 Interval observer 844.6 Experimental validation on Chlorella vulgaris culture 984.7 Conclusion 101Chapter 5 Bioprocess Control 1035.1 Determination of optimal operating conditions 1045.2 Generalities on control 1065.3 State of the art 1085.4 Generic Model Control 1105.5 Input/output linearizing control 1145.6 Nonlinear model predictive control 1195.7 Application to Chlorella vulgaris cultures 1325.8 Conclusion 144Conclusion 147Bibliography 153Index 173