Publications

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

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Y. Meng, N.S. Namachchivaya, N. Perkowski (2024). Almost Sure Asymptotic Stability of Parabolic SPDEs with Small Multiplicative Noise. Dynamical Systems.

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R. Zhou, Y. Meng, Z. Zeng, J. Liu (2024). Learning Koopman-based Stability Certificates for Unknown Nonlinear Systems. Submitted to 7th Annual Learning for Dynamics & Control Conference (L4DC), under review.

Z. Zeng, R. Zhou, Y. Meng, J. Liu (2024). Data-driven optimal control of unknown nonlinear dynamical systems using the Koopman operator. Submitted to 7th Annual Learning for Dynamics & Control Conference (L4DC), under review.

Y. Meng, R. Zhou, M. Ornik, J. Liu (2024). Resolvent-Type Data-Driven Learning of Generators for Unknown Continuous-Time Dynamical Systems. Submitted to IEEE Transaction on Automatic Control, under review.

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

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).

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

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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).

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

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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).

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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).

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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.

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

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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.

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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).

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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.

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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.

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

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Y. Meng, J. Liu (2023). Lyapunov-Barrier Characterization of Robust Reach-Avoid-Stay Specifications for Hybrid Systems. Nonlinear Analysis: Hybrid Systems.

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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).

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

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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).

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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).

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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.

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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).

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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).

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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).

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J. Sachs, Y. Meng, S. Giarola, A. Hawkes (2019). An agent-based model for energy investment decisions in the residential sector. Energy.