Formal synthesis of controllers for safety-critical autonomous systems: Developments and challenges
In recent years, formal methods have been extensively used in the design of autonomous
systems. By employing mathematically rigorous techniques, formal methods can provide …
systems. By employing mathematically rigorous techniques, formal methods can provide …
Probabilities are not enough: Formal controller synthesis for stochastic dynamical models with epistemic uncertainty
Capturing uncertainty in models of complex dynamical systems is crucial to designing safe
controllers. Stochastic noise causes aleatoric uncertainty, whereas imprecise knowledge of …
controllers. Stochastic noise causes aleatoric uncertainty, whereas imprecise knowledge of …
Formal verification of unknown dynamical systems via Gaussian process regression
Leveraging autonomous systems in safety-critical scenarios requires verifying their
behaviors in the presence of uncertainties and black-box components that influence the …
behaviors in the presence of uncertainties and black-box components that influence the …
Data-driven abstractions for verification of linear systems
We introduce a novel approach for the construction of symbolic abstractions-simpler, finite-
state models-which mimic the behaviour of a system of interest, and are commonly utilized to …
state models-which mimic the behaviour of a system of interest, and are commonly utilized to …
Sampling Performance of Periodic Event-Triggered Control Systems: a Data-driven Approach
We employ the scenario optimisation theory to compute a traffic abstraction, with probability
guarantees of correctness, of a PETC system with unknown dynamics from a finite number of …
guarantees of correctness, of a PETC system with unknown dynamics from a finite number of …
Data-driven abstractions for verification of deterministic systems
A common technique to verify complex logic specifications for dynamical systems is the
construction of symbolic abstractions: simpler, finite-state models whose behaviour mimics …
construction of symbolic abstractions: simpler, finite-state models whose behaviour mimics …
Data-driven safe controller synthesis for deterministic systems: A posteriori method with validation tests
In this work, we investigate the data-driven safe control synthesis problem for unknown
dynamic systems. We first formulate the safety synthesis problem as a robust convex …
dynamic systems. We first formulate the safety synthesis problem as a robust convex …
Data-Driven Abstractions for Control Systems
At the intersection of dynamical systems, control theory, and formal methods lies the
construction of symbolic abstractions: these typically represent simpler, finite-state models …
construction of symbolic abstractions: these typically represent simpler, finite-state models …
Scenario Approach and Conformal Prediction for Verification of Unknown Systems via Data-Driven Abstractions
Verification of uncertain, complex dynamical systems is crucial in the modern day world. An
increasingly common method to verify complex logic specifications for dynamical systems …
increasingly common method to verify complex logic specifications for dynamical systems …
Enhancing Data-Driven Stochastic Control via Bundled Interval MDP
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 …
controllers using a correct-by-design framework. We investigate a novel scheme to obtain …