4 papers · 1 filter
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…
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…
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…
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…