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eess.SY2025

Existence and Synthesis of Multi-Resolution Approximate Bisimulations for Continuous-State Dynamical Systems

Rudi Coppola, Yannik Schnitzer, Mirco Giacobbe +2

We present a fully automatic framework for synthesising compact, finite-state deterministic abstractions of deterministic, continuous-state autonomous systems under locally specifi…

eess.SY2025

Reinforcement Learning for Robust Ageing-Aware Control of Li-ion Battery Systems with Data-Driven Formal Verification

Rudi Coppola, Hovsep Touloujian, Pierfrancesco Ombrini +1

Rechargeable lithium-ion (Li-ion) batteries are a ubiquitous element of modern technology. In the last decades, the production and design of such batteries and their adjacent embed…

eess.SY2025

Memory-dependent abstractions of stochastic systems through the lens of transfer operators

Adrien Banse, Giannis Delimpaltadakis, Luca Laurenti +2

With the increasing ubiquity of safety-critical autonomous systems operating in uncertain environments, there is a need for mathematical methods for formal verification of stochast…

eess.SY2024

Temporal Logic Control for Nonlinear Stochastic Systems Under Unknown Disturbances

Ibon Gracia, Luca Laurenti, Manuel Mazo +2

In this paper, we present a novel framework to synthesize robust strategies for discrete-time nonlinear systems with random disturbances that are unknown, against temporal logic sp…

eess.SY2024

Data-driven Interval MDP for Robust Control Synthesis

Rudi Coppola, Andrea Peruffo, Licio Romao +2

The abstraction of dynamical systems is a powerful tool that enables the design of feedback controllers using a correct-by-design framework. We investigate a novel scheme to obtain…

eess.SY2024

Data-Driven Abstractions for Control Systems via Random Exploration

Rudi Coppola, Andrea Peruffo, Manuel Mazo

At the intersection of dynamical systems, control theory, and formal methods lies the construction of symbolic abstractions: these typically represent simpler, finite-state models…