2 citations · 9 across the 21 of their papers we have counts for
4 papers · 1 filter
Stability Analysis of Switched Linear Systems with Neural Lyapunov Functions
Virginie Debauche, Alec Edwards, Raphael M. Jungers +1
Neural-based, data-driven analysis and control of dynamical systems have been recently investigated and have shown great promise, e.g. for safety verification or stability analysis…
Data-driven abstractions via adaptive refinements and a Kantorovich metric [extended version]
Adrien Banse, Licio Romao, Alessandro Abate +1
We introduce an adaptive refinement procedure for smart, and scalable abstraction of dynamical systems. Our technique relies on partitioning the state space depending on the observ…
Learning stability guarantees for constrained switching linear systems from noisy observations
Adrien Banse, Zheming Wang, Raphaël M. Jungers
We present a data-driven framework based on Lyapunov theory to provide stability guarantees for a family of hybrid systems. In particular, we are interested in the asymptotic stabi…
Learning stability of partially observed switched linear systems
Zheming Wang, Raphaël M. Jungers, Mihály Petreczky +2
This paper deals with learning stability of partially observed switched linear systems under arbitrary switching. Such systems are widely used to describe cyber-physical systems wh…