Analyse, ingénierie et contrôle des micro-organismes (MICROCOSME), Centre Inria de l'Université Grenoble Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Grenoble Alpes (UGA), BIOP - Fluctuations, Régulation et Evolution des Systèmes Vivants (BIOP-LIPhy), Laboratoire Interdisciplinaire de Physique [Saint Martin d’Hères] (LIPhy), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Modélisation et commande de systèmes biologiques et écologiques (MACBES), Centre Inria d'Université Côte d'Azur, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut de pharmacologie moléculaire et cellulaire (IPMC), Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UniCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UniCA)-Institut Sophia Agrobiotech (ISA), Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Côte d'Azur (UniCA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Côte d'Azur (UniCA), IEEE, ANR-20-CE45-0014,Ctrl-AB,Optimisation et controle de la productivité d'un écosystème algues-bactéries(2020)
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CDC 2025 - 64th IEEE Conference on Decision and Control. :1-7
Microalgae are an important source of precursors (e.g. lipids) for a variety of biosynthetic processes (e.g. biofuel production). Their co-culturing with other organisms providing essential substrates for growth may reduce cost and provide new handles to control and robustify the production process. In previous work, we have introduced a nonlinear ordinary differential equation model for an optogenetically controllable algal-bacterial consortium, and studied maximization of algal biomass productivity in a continuous-flow bioreactor relative to optogenetic action and dilution rate. In this work, we expand the investigation of steady-state production performance for different objective criteria and control knobs. We additionally consider a yield criterion and a cost criterion, as well as a multiobjective optimization problem whose solution is shown to directly relate with a notion of net process profit. We investigate dependence of the optimal solutions on all the available bioprocess control knobs (optogenetics, dilution rate, richness of input medium), providing analytical results to characterize the solutions from different criteria and the relations among them, as well as simulations illustrating our results for a realistic set of biological system parameters.
