Regional stability conditions for recurrent neural network-based control systems
Systems and Control
2024-09-25 v1 Systems and Control
Abstract
In this paper we propose novel global and regional stability analysis conditions based on linear matrix inequalities for a general class of recurrent neural networks. These conditions can be also used for state-feedback control design and a suitable optimization problem enforcing H2 norm minimization properties is defined. The theoretical results are corroborated by numerical simulations, showing the advantages and limitations of the methods presented herein.
Keywords
Cite
@article{arxiv.2409.15792,
title = {Regional stability conditions for recurrent neural network-based control systems},
author = {Alessio La Bella and Marcello Farina and William D'Amico and Luca Zaccarian},
journal= {arXiv preprint arXiv:2409.15792},
year = {2024}
}