Our research in area of control systems covers both methodological developments and concrete applications. It addresses analysis, modeling, and control problems in fields ranging from biology to power systems engineering. Methodological developments concern, among others, hybrid systems, delay systems, and model predictive control, with a particular emphasis on nonlinear systems. These activities are often carried out in the framework of international collaborations or industrial partnerships.
Model predictive control, robustness, and optimization
Infinite dimensional systems (PDEs and delays)
Hybrid, switched, and sampled-data systems
Fields of application
Energy (power systems, electric motors, electric power conversion, smart-grids, etc.)
Robots and Vehicles (tele/co-manipulation, EV, UAV, etc.)
Life sciences (biomedical engineering, bio-reactors, neurosciences, etc.)
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Teams
COMEDY
The COMEDY team is interested in the analysis of structural properties and control of classes of dynamical systems such as non linear, hybrid, quantum and systems described by partial differential equations. The main focus is on fundamental results, but with a strong link to applications. Among the fields of application we recall: the analysis of neurophysiological systems, active vibration control, real-time scheduling, control of networked systems, control of quantum systems.
The MODESTY team is interested in system modelling, estimation and analysis of dynamical systems. The main theoretical axes are identification, observation, stability and delays, with a particular interest in applications to life sciences.
Les principaux axes de développements méthodologiques de l’équipe SYCOMORE couvrent un large spectre d’approches théoriques allant de la modélisation et de l’estimation (en particulier robuste) à la commande des systèmes complexes incertains sous contraintes et aux outils de diagnostic et reconfiguration de ces systèmes. Pour cela, les lois de commande (prédictive, robuste, non linéaire, etc.) élaborées font appel à des techniques d’optimisation fondées sur des heuristiques spécifiques. Elles s’orientent également vers des structures distribuées/décentralisées adaptées à la maitrise des systèmes cyber-physiques.
