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Team

Systèmes non linéaires et complexité
Team manager : Gildas BESANÇON    Mirko FIACCHINI

SYSCO is a research group in control whose main fields of interest lie in nonlinear and complex systems, from both  theoretical and application points of view. This means that it cares about rigorous formal analysis and results, as well as effective applicability of the developed methodologies on real processes. In its studies, it explicitly takes into account model nonlinearities, but also an increasing complexity both in system descriptions (high dimensions, constraints, hybrid dynamics...) and in application requirements (industrial demands, environmental norms...).


SYSCO research mainly relies on nonlinear systems theory, observers, predictive control, optimization, Lyapunov methods, and focuses on  nonlinear models, infinite dimensional systems, discrete-event or hybrid systems. Its main applications of interest lie in the broad fields of energy, environment, processes, robotics, mechatronics, and extends to computers or health.



News
CommuniquéAmiral technology lauréate du AI Challenge Paris Région 2018

Amiral technology, start-up issue de GIPSA-lab, fait partie du palmarés des 10 start-up sélectionnées au AI Challenge Paris Région 2018, organisé par la Région Ile de France. Amiral technology propose des solutions de maintenance prédictive industrielle et bénéficiera d'un accompagnement très poussé pendant 3 mois.

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Last publications of team

Method for controlling a microgrid

Dobrowolski Jean, David Gualino, Mazen Alamir, Seddik Bacha. Method for controlling a microgrid. Germany, Patent n° : 17306616.8 - 1202. 2018. 〈hal-01686935〉

Numerical investigation regarding an MPC scheme with non uniformly weighted stage cost without terminal constraints: Application to the control of a real-life cryogenic plant

Mazen Alamir. Numerical investigation regarding an MPC scheme with non uniformly weighted stage cost without terminal constraints: Application to the control of a real-life cryogenic plant. IFAC Workshop on Nonlinear Model Predictive Control NMPC2018, Aug 2018, Madison, United States. 〈hal-01811886〉

Local Input-to-State Stabilization of 1-D Linear Reaction-Diffusion Equation with Bounded Feedback

Aneel Tanwani, Swann Marx, Christophe Prieur. Local Input-to-State Stabilization of 1-D Linear Reaction-Diffusion Equation with Bounded Feedback. 23rd International Symposium on Mathematical Theory of Networks and Systems (MTNS2018) , Jul 2018, Hong Kong, China. 6p., 2018. 〈hal-01785104〉


Voir toutes les publications de l'équipe dans HAL
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