28 citations · 74 across the 24 of their papers we have counts for
4 papers · 1 filter
Towards Learning and Verifying Maximal Lyapunov-Barrier Functions with a Zubov PDE Formulation
Yiming Meng, Jun Liu
Verifying stability and safety guarantees for nonlinear systems has received considerable attention in recent years. This property serves as a fundamental building block for specif…
Verifying Probabilistic Regions of Attraction with Neural Lyapunov Functions for Stochastic Systems
Yun Su, Hans De Sterck, Jun Liu
Leveraging a stochastic extension of Zubov's equation, we develop a physics-informed neural network (PINN) approach for learning a neural Lyapunov function that captures the larges…
Safe Domains of Attraction for Discrete-Time Nonlinear Systems: Characterization and Verifiable Neural Network Estimation
Mohamed Serry, Haoyu Li, Ruikun Zhou +2
Analysis of nonlinear autonomous systems typically involves estimating domains of attraction, which have been a topic of extensive research interest for decades. Despite that, accu…
Stability of Jordan Recurrent Neural Network Estimator
Avneet Kaur, Ruikun Zhou, Jun Liu +1
State estimation refers to determining the states of a dynamical system that starts from a noisy initial condition and evolves under process noise, based on noisy measurements and…