PhD thesis: Data-driven stability analysis
Abstract: The thesis focuses on data-driven stability analysis of nonlinear dynamical systems without relying on explicit system models. The main objective is to certify equilibrium stability and compute regions of attraction directly from data using Lyapunov-based methods and convex optimisation techniques. The proposed frameworks bridge optimisation, learning, and Lyapunov theory, providing constructive and interpretable tools for model-free stability analysis.
Duration: October 2024 – September 2027
Supervision team: Sorin Olaru (HDR, L2S CentraleSupélec) – Matteo Tacchi-Bénard (GIPSA-lab CNRS)
