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eess.SY2026
Universal Approximation of Maximal Lyapunov Functions with Anchored Neural Networks
Jun Liu
Maximal Lyapunov functions encode the entire domain of attraction of an asymptotically stable equilibrium, but preserving strict decrease under neural approximation is difficult be…
eess.SY2026
Verifiable Error Bounds for Physics-Informed Neural KKL Observers
Hannah Berin-Costain, Harry Wang, Kirsten Morris +1
This paper proposes a computable state-estimation error bound for learning-based Kazantzis--Kravaris/Luenberger (KKL) observers. Recent work learns the KKL transformation map with…
eess.SY2026
Verifiable Error Bounds for Physics-Informed Neural Network Solutions of Lyapunov and Hamilton-Jacobi-Bellman Equations
Jun Liu
Many core problems in nonlinear systems analysis and control can be recast as solving partial differential equations (PDEs) such as Lyapunov and Hamilton-Jacobi-Bellman (HJB) equat…