most citedData-driven invariant set for nonlinear systems with application to command governors

4 citations · 4 across the 2 of their papers we have counts for

collaborators

5 papers

eess.SY2026

Data-Driven Personalization of Automated Insulin Delivery

Ali Kashani, Ali Tavasoli, Heman Shakeri

Automated insulin delivery (AID) systems are often tuned for the population and offer limited online adaptation to the inter- and intrapatient variability in insulin needs caused b…

eess.SY20264 cited

Data-driven invariant set for nonlinear systems with application to command governors

Ali Kashani, Claus Danielson

This paper presents a novel approach to synthesize positive invariant sets for unmodeled nonlinear systems using direct data-driven techniques. The data-driven invariant sets are u…

eess.SY2025

Learning Control Barrier Functions with Deterministic Safety Guarantees

Amy K. Strong, Ali Kashani, Claus Danielson +1

Barrier functions (BFs) characterize safe sets of dynamical systems, where hard constraints are never violated as the system evolves over time. Computing a valid safe set and BF fo…

eess.SY2025

Data driven synthesis of provable invariant sets via stochastically sampled data

Amy K. Strong, Ali Kashani, Claus Danielson +1

Positive invariant (PI) sets are essential for ensuring safety, i.e. constraint adherence, of dynamical systems. With the increasing availability of sampled data from complex (and…

eess.SY2025

Data-driven certificates of constraint enforcement and stability for unmodeled, discrete dynamical systems using tree data structures

Amy K. Strong, Ali Kashani, Claus Danielson +1

This paper addresses the critical challenge of developing data-driven certificates for the stability and safety of unmodeled dynamical systems by leveraging a tree data structure a…