Predictive Control Lab
The Predictive Control Lab develops the theory and computational methodologies for high performance control of fast and/or large scale dynamically interconnected systems. We do fundamental theoretical and applied research on predictive, or optimization-based controllers, with a focus on developing theoretically certifiable, practically sound, control methodologies that can incorporate holistic design criteria. Our research is inspired by the myriad control challenges involved in the integration of renewable power generation into the global energy mix, as well as the advanced planning and control challenges arising highly dynamic robotic applications.
The Predictive Control Lab is part of the Laboratoire d’Automatique.
New PhD Thesis
The public defence of the thesis of Seyed Sohail Madani entitled "Data-Driven Power Electronic Converter Control Design in Power System Application" was held on Friday 28th, November 2022.
Top cited paper at the Control Engineering Practice journal
The paper entitled "Data-driven methods for building control — A review and promising future directions", authored by Emilio T. Maddalena, Yingzhao Lian, and Colin N. Jones reached the "Top cited" category in the Control Engineering Practice journal!