Communication Dans Un Congrès Année : 2025

Sequentially learning regions of attraction from data

Résumé

The paper is dedicated to data-driven analysis of dynamical systems. It deals with certifying the basin of attraction of a stable equilibrium for an unknown dynamical system. It is supposed that point-wise evaluation of the right-hand side of the ordinary differential equation governing the system is available for a set of points in the state space. Technically, a Piecewise Affine Lyapunov function will be constructed iteratively using an optimisation-based technique for the effective validation of the certificates. As a main contribution, whenever those certificates are violated locally, a refinement of the domain and the associated tessellation is produced, thus leading to an improvement in the description of the domain of attraction.

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Dates et versions

hal-05059632 , version 1 (07-05-2025)

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Oumayma Khattabi, Matteo Tacchi, Sorin Olaru. Sequentially learning regions of attraction from data. MED 2025 - 33rd Mediterranean Conference on Control and Automation, Jun 2025, Tangier, Morocco. pp.589-594, ⟨10.1109/MED64031.2025.11073289⟩. ⟨hal-05059632⟩
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