Convex computation of regions of attraction from data using Sums-of-Squares programming

Fuente: arXiv
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Main Authors: Khattabi, Oumayma, Tacchi, Matteo, Olaru, Sorin
Format: Preprint
Published: 2025
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author Khattabi, Oumayma
Tacchi, Matteo
Olaru, Sorin
author_facet Khattabi, Oumayma
Tacchi, Matteo
Olaru, Sorin
contents 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 of 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.
format Preprint
id arxiv_https___arxiv_org_abs_2507_14073
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Convex computation of regions of attraction from data using Sums-of-Squares programming
Khattabi, Oumayma
Tacchi, Matteo
Olaru, Sorin
Systems and Control
Optimization and Control
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 of 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.
title Convex computation of regions of attraction from data using Sums-of-Squares programming
topic Systems and Control
Optimization and Control
url https://arxiv.org/abs/2507.14073