28 citations · 82 across the 18 of their papers we have counts for
4 papers · 1 filter
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…
Learning Regions of Attraction in Unknown Dynamical Systems via Zubov-Koopman Lifting: Regularities and Convergence
Yiming Meng, Ruikun Zhou, Jun Liu
The estimation for the region of attraction (ROA) of an asymptotically stable equilibrium point is crucial in the analysis of nonlinear systems. There has been a recent surge of in…
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…
Towards Learning and Verifying Maximal Neural Lyapunov Functions
Jun Liu, Yiming Meng, Maxwell Fitzsimmons +1
The search for Lyapunov functions is a crucial task in the analysis of nonlinear systems. In this paper, we present a physics-informed neural network (PINN) approach to learning a…