28 citations · 74 across the 24 of their papers we have counts for
4 papers · 1 filter
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…
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…
Physics-Informed Neural Network Lyapunov Functions: PDE Characterization, Learning, and Verification
Jun Liu, Yiming Meng, Maxwell Fitzsimmons +1
We provide a systematic investigation of using physics-informed neural networks to compute Lyapunov functions. We encode Lyapunov conditions as a partial differential equation (PDE…
Harmonic Control Lyapunov Barrier Functions for Constrained Optimal Control with Reach-Avoid Specifications
Amartya Mukherjee, Ruikun Zhou, Haocheng Chang +1
This paper introduces harmonic control Lyapunov barrier functions (harmonic CLBF) that aid in constrained control problems such as reach-avoid problems. Harmonic CLBFs exploit the…