Convex computation of regions of attraction from data using sums-of-squares programming
Abstract
This paper focuses on the analysis of the Region of Attraction (RoA) for unknown autonomous dynamical systems. A data-driven approach based on the moment-Sum of Squares (SoS) hierarchy is proposed, enabling novel RoA outer approximations despite the reduced information on the dynamics. The main contribution consists in bypassing the system model and, hence, the recurring constraint on its polynomial structure. Numerical experiments showcase the influence of data on learned approximating sets, highlighting the potential of this method.
Fields of Study & Subjects
Model Reduction and Neural Networks
Control Systems and Identification
Advanced Control Systems Optimization
Publication details
- Journal / source
- IFAC Journal of Systems and Control
- Publisher
- Elsevier BV
- Volume
- 35
- Pages
- 100361–100361
- Publication date
- 6 January 2026
- Language
- EN