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Authors: Benjamin Bocquillon 1 ; Philippe Feyel 1 ; Guillaume Sandou 2 and Pedro Rodriguez-Ayerbe 2

Affiliations: 1 Safran Electronics & Defense, 100 avenue de Paris, Massy, France ; 2 L2S, CentraleSupélec, CNRS, Université Paris-Saclay, 3 rue Joliot Curie, 91192 Gif-Sur-Yvette, France

Keyword(s): Lyapunov Function, Domain of Attraction, Optimization, Neural Network, Nonlinear System.

Abstract: This work deals with a new method for computing Lyapunov functions represented by neural networks for autonomous nonlinear systems. Based on the Lyapunov theory and the notion of domain of attraction, we propose an optimization method for determining a Lyapunov function modelled by a neural network while maximizing the domain of attraction. The potential of the proposed method is demonstrated by simulation examples.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Bocquillon, B.; Feyel, P.; Sandou, G. and Rodriguez-Ayerbe, P. (2020). Efficient Construction of Neural Networks Lyapunov Functions with Domain of Attraction Maximization. In Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics - ICINCO; ISBN 978-989-758-442-8; ISSN 2184-2809, SciTePress, pages 174-180. DOI: 10.5220/0009883401740180

@conference{icinco20,
author={Benjamin Bocquillon. and Philippe Feyel. and Guillaume Sandou. and Pedro Rodriguez{-}Ayerbe.},
title={Efficient Construction of Neural Networks Lyapunov Functions with Domain of Attraction Maximization},
booktitle={Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics - ICINCO},
year={2020},
pages={174-180},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009883401740180},
isbn={978-989-758-442-8},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics - ICINCO
TI - Efficient Construction of Neural Networks Lyapunov Functions with Domain of Attraction Maximization
SN - 978-989-758-442-8
IS - 2184-2809
AU - Bocquillon, B.
AU - Feyel, P.
AU - Sandou, G.
AU - Rodriguez-Ayerbe, P.
PY - 2020
SP - 174
EP - 180
DO - 10.5220/0009883401740180
PB - SciTePress