Stochastic hybrid systems have received significant attentions as a relevant modeling
framework describing many systems, from engineering to the life sciences: they enable the …

This letter is concerned with develo** a data-driven approach for learning control barrier
certificates (CBCs) and associated safety controllers for discrete-time input-affine nonlinear …

A barrier certificate, defined over the states of a dynamical system, is a real-valued function
whose zero level set characterizes an inductively verifiable state invariant separating …

This paper is concerned with a compositional scheme for the construction of control barrier
certificates for interconnected discrete-time stochastic systems. The main objective is to …

Barrier certificates provide functional overapproximations for the reachable set of dynamical
systems and provide inductive guarantees on the safe evolution of the system. Formally a …

In this work, we propose a compositional scheme based on small-gain reasoning for the
safety controller synthesis of interconnected stochastic hybrid systems with both continuous …

In this article, we propose a compositional framework for the synthesis of safety controllers
for networks of partially observable discrete-time stochastic control systems (also known as …

We introduce a compositional data-driven methodology for designing fully-decentralized
safety controllers applicable to large-scale interconnected networks, encompassing …

This work is concerned with a compositional data-driven approach for formal safety
verification of large-scale continuous-time dynamical systems with unknown models. The …

This letter addresses the problem of synthesizing controllers that enforce properties
expressed by Universal Co-Büchi Automata (UCA) over stochastic control systems. Our …