Control of Nonlinear Systems with Reach-Avoid-Stay Specifications: A Lyapunov-Barrier Approach with an Application to the Moore-Greizer Model. - Yiming Meng; Yinan Li 001; Jun Liu 015 (ACC, 2021)

Safety-Critical Control of Stochastic Systems using Stochastic Control Barrier Functions. - Chuanzheng Wang; Yiming Meng; Stephen L. Smith 001; Jun Liu 015 (CDC, 2021)

Learning Control Barrier Functions with High Relative Degree for Safety-Critical Control. - Chuanzheng Wang; Yiming Meng; Yinan Li 001; Stephen L. Smith 001; Jun Liu 015 (ECC, 2021)

Sufficient Conditions for Robust Probabilistic Reach-Avoid-Stay Specifications using Stochastic Lyapunov-Barrier Functions. - Yiming Meng; Jun Liu 015 (ACC, 2022)

Data-Driven Learning of Safety-Critical Control with Stochastic Control Barrier Functions. - Chuanzheng Wang; Yiming Meng; Stephen L. Smith 001; Jun Liu 015 (CDC, 2022)

Robustly Complete Finite-State Abstractions for Verification of Stochastic Systems. - Yiming Meng; Jun Liu 015 (FORMATS, 2022)

Smooth converse Lyapunov-barrier theorems for asymptotic stability with safety constraints and reach-avoid-stay specifications. - Yiming Meng; Yinan Li 001; Maxwell Fitzsimmons; Jun Liu 015 (Autom., 2022)

Towards Learning and Verifying Maximal Neural Lyapunov Functions. - Jun Liu 015; Yiming Meng; Maxwell Fitzsimmons; Ruikun Zhou (CDC, 2023)

Robustly Complete Finite-State Abstractions for Control Synthesis of Stochastic Systems. - Yiming Meng; Jun Liu 015 (CoRR, 2023)

Stochastic Control Barrier Functions with Bayesian Inference for Unknown Stochastic Differential Equations. - Chuanzheng Wang; Yiming Meng; Jun Liu 015; Stephen L. Smith 001 (CoRR, 2023)

Hopf Bifurcations of Moore-Greitzer PDE Model with Additive Noise. - Yiming Meng; Navaratnam Sri Namachchivaya; Nicolas Perkowski (J. Nonlinear Sci., 2023)

LyZNet with Control: Physics-Informed Neural Network Control of Nonlinear Systems with Formal Guarantees. - Jun Liu 015; Yiming Meng; Ruikun Zhou (ADHS, 2024)

Compositionally Verifiable Vector Neural Lyapunov Functions for Stability Analysis of Interconnected Nonlinear Systems. - Jun Liu 015; Yiming Meng; Maxwell Fitzsimmons; Ruikun Zhou (ACC, 2024)

Zubov-Koopman Learning of Maximal Lyapunov Functions. - Yiming Meng; Ruikun Zhou; Jun Liu 015 (ACC, 2024)

Koopman-Based Learning of Infinitesimal Generators without Operator Logarithm. - Yiming Meng; Ruikun Zhou; Melkior Ornik; Jun Liu 015 (CDC, 2024)

TOOL LyZNet: A Lightweight Python Tool for Learning and Verifying Neural Lyapunov Functions and Regions of Attraction. - Jun Liu 015; Yiming Meng; Maxwell Fitzsimmons; Ruikun Zhou (HSCC, 2024)

Physics-Informed Neural Networks for Stability Analysis and Control with Formal Guarantees. - Jun Liu 015; Yiming Meng; Maxwell Fitzsimmons; Ruikun Zhou (HSCC, 2024)

Physics-Informed Neural Network Policy Iteration: Algorithms, Convergence, and Verification. - Yiming Meng; Ruikun Zhou; Amartya Mukherjee; Maxwell Fitzsimmons; Christopher Song; Jun Liu 015 (ICML, 2024)

Koopman-Based Data-Driven Techniques for Adaptive Cruise Control System Identification. - Yiming Meng; Hangyu Li; Melkior Ornik; Xiaopeng Li (ITSC, 2024)

LyZNet: A Lightweight Python Tool for Learning and Verifying Neural Lyapunov Functions and Regions of Attraction. - Jun Liu 015; Yiming Meng; Maxwell Fitzsimmons; Ruikun Zhou (CoRR, 2024)

Learning Koopman-based Stability Certificates for Unknown Nonlinear Systems. - Ruikun Zhou; Yiming Meng; Zhexuan Zeng; Jun Liu 015 (CoRR, 2024)

Physics-Informed Extreme Learning Machine Lyapunov Functions. - Ruikun Zhou; Maxwell Fitzsimmons; Yiming Meng; Jun Liu 015 (IEEE Control. Syst. Lett., 2024)

Stochastic Lyapunov-Barrier Functions for Robust Probabilistic Reach-Avoid-Stay Specifications. - Yiming Meng; Jun Liu 015 (IEEE Trans. Autom. Control., 2024)

Formally Verified Physics-Informed Neural Control Lyapunov Functions. - Jun Liu 015; Maxwell Fitzsimmons; Ruikun Zhou; Yiming Meng (ACC, 2025)

Data-driven optimal control of unknown nonlinear dynamical systems using the Koopman operator. - Zhexuan Zeng; Ruikun Zhou; Yiming Meng; Jun Liu 015 (L4DC, 2025)

Pseudo-Target Optimization Strategy Based on Policy Iteration Algorithm. - Yiming Meng; Daichen Liu; Ziyuan Wang (IEEE Access, 2025)

Physics-informed neural network Lyapunov functions: PDE characterization, learning, and verification. - Jun Liu 015; Yiming Meng; Maxwell Fitzsimmons; Ruikun Zhou (Autom., 2025)

Koopman Spectral Analysis and System Identification for Stochastic Dynamical Systems via Yosida Approximation of Generators. - Jun Zhou; Yiming Meng; Jun Liu 015 (CoRR, 2025)