Preprints

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

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

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

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

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

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

• Y. Meng, N.S. Namachchivaya, and N. Perkowski, "Almost Sure Asymptotic Stability of Parabolic SPDEs with Small Multiplicative Noise: With Application to the Perturbed Moore-Greitzer Model," submitted to Dynamical Systems: An International Journal, under review.

• C. Wang, Y. Meng (equal contribution), Y. Li, S.L. Smith, and J. Liu, "Learning Control Barrier Functions with High Relative Degree for Safety-Critical Control," submitted to European Journal of Control, under review.

Journal Articles

• (TAC'23) Y. Meng and J. Liu, "Stochastic Lyapunov-Barrier Functions for Robust Probabilistic Reach-Avoid-Stay Specifications," IEEE Transitions on Automatic Control, to appear, 2024. 

• (OJCSYS'23) Y. Meng and J. Liu, "Robustly Complete Finite-State Abstractions for Control Synthesis of Stochastic Systems," IEEE Open Journal of Control Systems, Vol. 2 (pp.235-248), 2023.

• (JNLS'23) Y. Meng, N.S. Namachchivaya, and N. Perkowski, "Hopf Bifurcations of Moore-Greitzer PDE Model with Additive Noise," Journal of Nonlinear Science, Vol. 33 (74), 2023.

• (NAHS'23) Y. Meng and J. Liu, "Lyapunov-Barrier Characterization of Robust Reach-Avoid-Stay Specifications for Hybrid Systems," Nonlinear Analysis: Hybrid Systems, Vol. 49 (101340), 2023.

• (Automatica'22) Y. Meng, Y. Li, M. Fitzsimmons, and J. Liu, "Smooth Converse Lyapunov- Barrier Theorems for Asymptotic Stability with Safety Constraints and Reach-Avoid-Stay Specifications," Automatica, Vol. 144 (110478), 2022.

Machine Learning Conference Articles

• (ICML'24) Y. Meng, R.Zhou (equal contribution), A.Mukherjee, M.Fitzsimmons, C.Song, and J.Liu, "Physics-Informed Neural Policy Iteration: Algorithms, Convergence, and Verification", International Conference on Machine Learning (ICML), accepted, 2024.

Refereed Conference Articles

• (ADHS'24) J. Liu, Y. Meng, and R. Zhou, "LyZNet with Control: Physics-Informed Neural Network Control of Nonlinear Systems with Formal Guarantees", IFAC Conference on Analysis and Design of Hybrid Systems (ADHS), to appear, 2024.

• (ACC'24-2) Y. Meng, R. Zhou, and J. Liu, "Zubov-Koopman Learning of Maximal Lyapunov Functions," American Control Conference (ACC), to appear, 2024.

• (ACC'24-1) J. Liu, Y. Meng, M. Fitzsimmons, and R. Zhou, "Compositionally Verifiable Vector Neural Lyapunov Functions for Stability Analysis of Interconnected Nonlinear Systems," American Control Conference (ACC), to appear, 2024.

• (HSCC'24) J. Liu, Y. Meng, M. Fitzsimmons, and R. Zhou, "LyZNet: A Lightweight Python Tool for Learning and Verifying Neural Lyapunov Functions and Regions of Attraction," ACM International Conference on Hybrid Systems, Computation and Control (HSCC), to appear, 2024.

• (IUTAM'23) Y. Meng, N.S. Namachchivaya, and N. Perkowski, "Asymptotic Approximation of the Maximal Lyapunov Exponent of Moore-Greitzer PDE model with Multiplicative Noise close to Stall Bifurcation," International Union of Theoretical and Applied Mechanics (IUTAM) Symposium on Nonlinear Dynamics for design of mechanical systems across different length/time scales, to appear, 2023.

• (CDC'23) J. Liu, Y. Meng, M. Fitzsimmons, and R. Zhou, "Towards Learning and Verifying Maximal Neural Lyapunov Functions," IEEE Conference on Decision and Control (CDC), 2023.

• (CDC'22) C. Wang, Y. Meng (equal contribution), S.L. Smith, and J. Liu, "Data-Driven Learning of Safety-Critical Control with Stochastic Control Barrier Functions," IEEE Conference on Decision and Control (CDC), 2021.

• (FORMATS'22) Y. Meng and J. Liu, “Robustly Complete Finite-State Abstractions for Verification of Stochastic Systems," Formal Modeling and Analysis of Timed Systems 20th International Conference (FORMATS), 2022.

• (ACC'22) Y. Meng and J. Liu, "Sufficient Conditions for Robust Probabilistic Reach-Avoid-Stay Specifications using Stochastic Lyapunov-Barrier Functions," American Control Conference (ACC), 2022.

• (CDC'21) C. Wang, Y. Meng (equal contribution), S.L. Smith, and J. Liu, “Safety-Critical Control of Stochastic Systems using Stochastic Control Barrier Functions," IEEE Conference on Decision and Control (CDC), 2021.

• (ECC'21) C. Wang, Y. Meng, Y. Li, S.L. Smith, and J. Liu, "Learning Control Barrier Functions with High Relative Degree for Safety-Critical Control," European Control Conference (ECC), 2021.

• (ACC'21) Y. Meng, Y. Li, and J. Liu, "Control of Nonlinear Systems with Reach-Avoid-Stay Specifications: A Lyapunov-Barrier Approach with an Application to the Moore-Greizer Model," American Control Conference (ACC), 2021.

Dissertation

• (Ph.D. Thesis) Y. Meng, "Bifurcation and Robust Control of Instabilities in the Presence of Uncertainties", Ph.D. Thesis, University of Waterloo, October 2022.

Other Research Articles

• (Energy'19) J. Sachs, Y. Meng, S. Giarola, and A. Hawkes, "An agent-based model for energy investment decisions in the residential sector", Energy, Vol. 172, 2019.

• (Energy&Fuels'16) N. Jin, G. Wang, S. Han, Y. Meng, C.Xu, and J. Gao, "Hydroconversion Behavior of Asphaltenes under Liquid-Phase Hydrogenation Conditions," Journal of Energy & Fuels, Vol. 30, 2016.