no code implementations • 12 Apr 2024 • Rudi Coppola, Andrea Peruffo, Licio Romao, Alessandro Abate, Manuel Mazo Jr
The abstraction of dynamical systems is a powerful tool that enables the design of feedback controllers using a correct-by-design framework.
no code implementations • 16 Feb 2024 • Rudi Coppola, Andrea Peruffo, Manuel Mazo Jr
At the intersection of dynamical systems, control theory, and formal methods lies the construction of symbolic abstractions: these typically represent simpler, finite-state models whose behaviour mimics the one of an underlying concrete system but are easier to analyse.
no code implementations • 16 Nov 2023 • Alec Edwards, Andrea Peruffo, Alessandro Abate
This paper presents Fossil 2. 0, a new major release of a software tool for the synthesis of certificates (e. g., Lyapunov and barrier functions) for dynamical systems modelled as ordinary differential and difference equations.
no code implementations • 12 Sep 2023 • Alec Edwards, Andrea Peruffo, Alessandro Abate
An emerging branch of control theory specialises in certificate learning, concerning the specification of a desired (possibly complex) system behaviour for an autonomous or control model, which is then analytically verified by means of a function-based proof.
no code implementations • 3 Nov 2022 • Rudi Coppola, Andrea Peruffo, Manuel Mazo Jr
A common technique to verify complex logic specifications for dynamical systems is the construction of symbolic abstractions: simpler, finite-state models whose behaviour mimics the one of the systems of interest.
no code implementations • 10 Mar 2022 • Andrea Peruffo, Manuel Mazo Jr
We extend the scenario approach to multiclass SVM algorithms in order to construct a PAC map between the concrete, unknown state-space and the inter-sample times.
no code implementations • 21 Jul 2020 • Daniele Ahmed, Andrea Peruffo, Alessandro Abate
In this paper we employ SMT solvers to soundly synthesise Lyapunov functions that assert the stability of a given dynamical model.
no code implementations • 7 Jul 2020 • Andrea Peruffo, Daniele Ahmed, Alessandro Abate
We introduce an automated, formal, counterexample-based approach to synthesise Barrier Certificates (BC) for the safety verification of continuous and hybrid dynamical models.
no code implementations • 19 Mar 2020 • Alessandro Abate, Daniele Ahmed, Mirco Giacobbe, Andrea Peruffo
We employ a counterexample-guided approach where a numerical learner and a symbolic verifier interact to construct provably correct Lyapunov neural networks (LNNs).
