Publications

Y. Meng, R. Zhou, A. Mukherjee, M. Fitzsimmons, C. Song, J. Liu (2024). Physics-Informed Neural Network Policy Iteration: Algorithms, Convergence, and Verification. In 2024 International Conference on Machine Learning (ICML), to appear.

Y. Meng, R. Zhou, J. Liu (2024). Zubov-Koopman Learning of Maximal Lyapunov Functions. In 2024 American Control Conference (ACC).

J. Liu, Y. Meng, M. Fitzsimmons, R. Zhou (2024). Compositionally Verifiable Vector Neural Lyapunov Functions for Stability Analysis of Interconnected Nonlinear Systems. In 2024 American Control Conference (ACC).

PDF Cite Project

J. Liu, Y. Meng, M. Fitzsimmons, R. Zhou (2024). LyZNet: A Lightweight Python Tool for Learning and Verifying Neural Lyapunov Functions and Regions of Attraction. In 2024 ACM International Conference on Hybrid Systems: Computation and Control (HSCC).

PDF Cite Project

J. Liu, Y. Meng, R. Zhou (2024). LyZNet with Control: Physics-Informed Neural Network Control of Nonlinear Systems with Formal Guarantees. In 2024 IFAC Conference on Analysis and Design of Hybrid Systems (ADHS), to appear.

Y. Meng, H. Li, M. Ornik, X. Li (2024). Koopman-Based Data-Driven Techniques for Adaptive Cruise Control System Identification. submitted to 2024 IEEE International Conference on Intelligent Transportation Systems (ITSC), under review.

Y. Meng, R. Zhou, M. Ornik, J. Liu (2024). Koopman-Based Learning of Infinitesimal Generators without Operator Logarithm. submitted to 2024 IEEE Conference on Decision and Control (CDC), under review.

PDF Project Source Document

R. Zhou, M. Fitzsimmons, Y. Meng, J. Liu (2024). Physics-Informed Extreme Learning Machine Lyapunov Functions. submitted to IEEE Control Systems Letters, under review.

Y. Meng, T. Shafa, J. Wei, M. Ornik (2024). Online Learning and Control Synthesis for Reachable Paths of Unknown Nonlinear Systems. submitted to IEEE Transaction on Automatic Control, under review.

PDF Project Source Document

Y. Meng, J. Liu (2024). Stochastic Lyapunov-Barrier Functions for Robust Probabilistic Reach-Avoid-Stay Specifications. IEEE Transitions on Automatic Control.

PDF Cite Project DOI

J. Liu, Y. Meng, M. Fitzsimmons, R. Zhou (2024). Physics-Informed Neural Network Lyapunov Functions: PDE Characterization, Learning, and Verification. submitted to Automatica, under review.

PDF Project Source Document

Y. Meng, N.S. Namachchivaya, N. Perkowski (2024). Asymptotic Approximation of the Maximal Lyapunov Exponent of Moore-Greitzer PDE model with Multiplicative Noise close to Stall Bifurcation. submitted to Dynamical Systems (formerly known as Dynamics and Stability of Systems), under review.

J. Liu, Y. Meng, M. Fitzsimmons, R. Zhou (2023). Towards Learning and Verifying Maximal Neural Lyapunov Functions. In 2023 IEEE Conference on Decision and Control (CDC).

PDF Cite Project DOI

Y. Meng, R. Zhou, J. Liu (2023). Learning Regions of Attraction in Unknown Dynamical Systems via Zubov-Koopman Lifting: Regularities and Convergence. submitted to IEEE Transitions on Automatic Control, under review.

PDF Project Source Document

Y. Meng, N.S. Namachchivaya, N. Perkowski (2023). Asymptotic Approximation of the Maximal Lyapunov Exponent of Moore-Greitzer PDE model with Multiplicative Noise close to Stall Bifurcation. In International Union of Theoretical and Applied Mechanics (IUTAM) bookseries.

Y. Meng, J. Liu (2023). Robustly Complete Finite-State Abstractions for Control Synthesis of Stochastic Systems. IEEE Open Journal of Control Systems.

PDF Cite Project DOI

Y. Meng, N.S. Namachchivaya, N. Perkowski (2023). Hopf Bifurcations of Moore-Greitzer PDE Model with Additive Noise. Journal of Nonlinear Science.

PDF Cite Project DOI

Y. Meng, J. Liu (2023). Lyapunov-Barrier Characterization of Robust Reach-Avoid-Stay Specifications for Hybrid Systems. IEEE Transitions on Automatic Control.

PDF Cite Project DOI

C. Wang, Y. Meng, S.L. Smith, J. Liu (2022). Data-Driven Learning of Safety-Critical Control with Stochastic Control Barrier Functions. In 2022 IEEE Conference on Decision and Control (CDC).

PDF Cite Project DOI

Yiming Meng (2022). Bifurcation and Robust Control of Instabilities in the Presence of Uncertainties.

PDF Source Document

Y. Meng, J. Liu (2022). Robustly Complete Finite-State Abstractions for Verification of Stochastic Systems. In 2022 Formal Modeling and Analysis of Timed Systems International Conference (FORMATS).

PDF Cite Project DOI

Y. Meng, J. Liu (2022). Sufficient Conditions for Robust Probabilistic Reach-Avoid-Stay Specifications using Stochastic Lyapunov-Barrier Functions. In 2022 American Control Conference (ACC).

PDF Cite Project DOI

Y. Meng, Y. Li, M. Fitzzsimmons, J. Liu (2022). Smooth Converse Lyapunov-Barrier Theorems for Asymptotic Stability wit Safety Constraints and Reach-Avoid-Stay Specifications. Automatica.

PDF Cite Project DOI

C. Wang, Y. Meng, S.L. Smith, J. Liu (2021). Safety-Critical Control of Stochastic Systems using Stochastic Control Barrier Functions. In 2021 IEEE Conference on Decision and Control (CDC).

PDF Cite Project DOI

Y. Meng, Y. Li, J. Liu (2021). Control of Nonlinear Systems with Reach-Avoid-Stay Specifications: A Lyapunov-Barrier Approach with an Application to the Moore-Greizer Model. In 2021 American Control Conference (ACC).

PDF Cite Project DOI

C. Wang, Y. Meng, Y, Li, S.L. Smith, J. Liu (2021). Learning Control Barrier Functions with High Relative Degree for Safety-Critical Control. In 2021 European Control Conference (ECC).

PDF Cite Project DOI