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

Title:
Convex computation of regions of attraction from data using Sums-of-Squares programming
Authors:
Khattabi, Oumayma, Tacchi, Matteo, Olaru, Sorin
Contributors:
Laboratoire des signaux et systèmes (L2S), CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), GIPSA - Modelling and Optimal Decision for Uncertain Systems (GIPSA-MODUS), GIPSA Pôle Automatique et Diagnostic (GIPSA-PAD), Grenoble Images Parole Signal Automatique (GIPSA-lab), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP), Université Grenoble Alpes (UGA)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Grenoble Alpes (UGA)
Publisher Information:
CCSD, 2025.
Publication Year:
2025
Collection:
collection:UGA
collection:CNRS
collection:INPG
collection:GIPSA
collection:SUP_LSS
collection:CENTRALESUPELEC
collection:TDS-MACS
collection:UNIV-PARIS-SACLAY
collection:GIPSA-PAD
collection:GIPSA-MODUS
collection:UNIVERSITE-PARIS-SACLAY
collection:UGA-EPE
collection:GS-COMPUTER-SCIENCE
collection:GS-SPORT-HUMAN-MOVEMENT
collection:TEST-UGA
Subject Terms:
Data-driven analysis, SoS programming, Region of attraction approximation, Linear programming, [MATH.MATH-OC]Mathematics [math], Optimization and Control [math.OC]
Original Identifier:
HAL: hal-05379529
Document Type:
E-Ressource preprint<br />Preprints<br />Working Papers
Language:
English
Access URL:
https://hal.science/hal-05379529
https://hal.science/hal-05379529v1/document
https://hal.science/hal-05379529v1/file/Current_PhD_files___Oumayma.pdf
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edshal.hal.05379529v1
Database:
HAL

Weitere Informationen

The paper concentrates on the analysis of the Region of Attraction (RoA) for unknown autonomous dynamical systems. The aim is to explore a data-driven approach based on moment-Sum of Squares (SoS) hierarchy, which enables novel RoA outer approximations despite the reduced information on the structure of the dynamics. The main contribution of this work is bypassing the system model and, consequently, the recurring constraint on its polynomial structure. Numerical experimentation showcases the influence of data on learned approximating sets, offering a promising outlook on the potential of this method.