activity
20242026
collaborators

9 papers

eess.SY2026

Patching Control Lyapunov Barrier Functions for Temporal Logic Specifications with Bounded Controls

Ruikun Zhou, Yating Yuan, Haocheng Chang +2

We propose an abstraction-free framework for controller synthesis for continuous-time dynamical systems subject to Linear Temporal Logic (LTL) specifications and bounded control in…

math.DS2025

Resolvent-Type Data-Driven Learning of Generators for Unknown Continuous-Time Dynamical Systems

Yiming Meng, Ruikun Zhou, Melkior Ornik +1

A semigroup characterization, or equivalently, a characterization by the generator, is a classical technique used to describe continuous-time nonlinear dynamical systems. In the re…

math.OC2025

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…

eess.SY2025

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…

eess.SY2025

Learning Koopman-based Stability Certificates for Unknown Nonlinear Systems

Ruikun Zhou, Yiming Meng, Zhexuan Zeng +1

Koopman operator theory has gained significant attention in recent years for identifying discrete-time nonlinear systems by embedding them into an infinite-dimensional linear vecto…

math.OC2025

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…