AUT (AUTomatic Control) Team

The IETR's Automatic Control team develops algorithmic solutions for the control and analysis of large and interacting systems. Its main domain of application is energy: power grids, positive energy buildings...
AUT research team at CentraleSupélec, June 2023

Presentation & research topics

The team is composed of 7 permanent faculty members from CentraleSupélec. As of January 1, 2022, it (co-)hosts 6 PhD students.

The team is located on the Rennes campus of CentraleSupélec.

The Automatic team works both on :

  • methodological contributions to the analysis and control of dynamic systems, beyond any particular application domain
  • specific applied contributions to the energy domain, thanks to its experience in the context and specific technologies of power systems, energy in buildings and energy systems in general.

Methodological contributions

In terms of methodology, the team's work focuses on:

  • the distribution and prioritization of the analysis, identification, control and state estimation of dynamic systems, in particular hybrid systems
  • considering the safety and robustness of distributed control applications when one of the cooperating actors becomes non-cooperative

Contributions to the field of energy

Based on its methodological expertise, the contributes to the development of Smart Energy Systems, in particular through its work on:

  • efficiency of energy systems
  • energy management and the integration of Renewable Energies (RE) in positive energy buildings
  • integration of active buildings in energy distribution networks
  • active management of distribution grids and microgrids to ensure their optimal operation and enhance their flexibility

Projects

  • Smart building (Stanislav Aranovskiy, funding from Rennes Métropole)
  • Smart & Secure Room :Technical platform aimed at improving the resilience of smart grids against failures and cyber-attacks: study of vulnerabilities (hardware, software and human behavior) and implementation of resilient control laws. 
    • Funding: CentraleSupélec (55%), Rennes Métropole (30%), IETR (10%), IRISA (5%).

Ongoing PhD students

Alexandre Faye-Bédrin (2022-2025)

Data-driven Model Predictive Control (MPC)

Microgrid sizing under uncertainty

Elsy EL SAYEGH (2021 – 2024)

Optimal design of microgrids taking into account resilience and long-term uncertainty (e.g., changes in consumption or fuel prices over several years). Collaboration with industry: EDF labs.

Illustration of smart home controller

Alexis Wagner (2021 – 2024)

Smart home: Lifecycle analysis and benefits of advanced control systems (partnership with SATIE laboratory)

Convergence of estimator illustration

Marina Korotina (2020 – 2023)

Performance Enhancement in Adaptive and Learning Control Systems. Possible applications include model-predictive control with model adaptation and data-driven control for real-time power management. Double postgraduate program with ITMO University (Russia).

Alumni PhD students

Joy EL FEGHALI (2023)

Reduction of a multi-energy system model in Modelica. Application to an urban multi-energy network. Collaboration with EDF and L2S (RISEGrid institute).

Joy has become R&D engineer at the national French grid operator (TSO) RTE.

Rafael Accácio NOGUEIRA (2022)

Handling non cooperative agents in a distributed optimization framework.

Post-doctoral researcher at LAAS (CNRS), Toulouse

Xiang DAI (2021)

Dual decomposition for predictive control: accelerated termination in iterations.

Post-doc researcher at Gipsa-lab on aircraft navigation based on vision and inertial data

Jesse James PRINCE AGBODJAN (2021)

Design of resilient controllers for extreme and rare events in energy systems. Example: control of a microgrid with an energy storage taking into account the risk of failure of the main grid.

Jesse James has been Data scientist at the Distribution grid operator SRD, since 2022, after a postdoc in Reinforcement Learning at SATIE laboratory, ENS Rennes.

Amanda ABREU (2019)

Hybrid hierarchical model predictive control for energy management in buildings.

Industrial collaboration with Delta Dore.

Amanda has become R&D engineer in Automation & Control at DeltaDore since 2019.