Cover Image

Provably-Stable Neural Network-Based Control of Nonlinear Systems

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Anran, Swensen, John P., Hosseinzadeh, Mehdi
Format:	Preprint
Published:	2025
Subjects:	Optimization and Control Machine Learning Systems and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Guaranteed-Stable Neural Network Approach for Optimal Control of Nonlinear Systems
by: Li, Anran, et al.
Published: (2025)

A Block-Alternating Iterative Approach for a Class of Non-Convex Optimization Problems
by: Li, Anran, et al.
Published: (2026)

Distributed Control of Network Systems in the Space of Stabilizing Graph Neural Network Policies
by: Cao, John, et al.
Published: (2025)

Discrete-time Contraction-based Control of Nonlinear Systems with Parametric Uncertainties using Neural Networks
by: Wei, Lai, et al.
Published: (2021)

Neural Network-assisted Interval Reachability for Systems with Control Barrier Function-Based Safe Controllers
by: Ajeyemi, Damola, et al.
Published: (2025)

Neural Operators for Predictor Feedback Control of Nonlinear Delay Systems
by: Bhan, Luke, et al.
Published: (2024)

Forward Invariance in Neural Network Controlled Systems
by: Harapanahalli, Akash, et al.
Published: (2023)

Universal Approximation Power of Deep Residual Neural Networks via Nonlinear Control Theory
by: Tabuada, Paulo, et al.
Published: (2020)

Denoising Diffusion-Based Control of Nonlinear Systems
by: Elamvazhuthi, Karthik, et al.
Published: (2024)

A Nonlinear Separation Principle via Contraction Theory: Applications to Neural Networks, Control, and Learning
by: Gokhale, Anand, et al.
Published: (2026)

Neural Contraction Metrics with Formal Guarantees for Discrete-Time Nonlinear Dynamical Systems
by: Li, Haoyu, et al.
Published: (2025)

Contraction-Guided Adaptive Partitioning for Reachability Analysis of Neural Network Controlled Systems
by: Harapanahalli, Akash, et al.
Published: (2023)

Sampling-Horizon Neural Operator Predictors for Nonlinear Control under Delayed Inputs
by: Bhan, Luke, et al.
Published: (2026)

Score Matching Diffusion Based Feedback Control and Planning of Nonlinear Systems
by: Elamvazhuthi, Karthik, et al.
Published: (2025)

System-level Safety Guard: Safe Tracking Control through Uncertain Neural Network Dynamics Models
by: Li, Xiao, et al.
Published: (2023)

RHYME-XT: A Neural Operator for Spatiotemporal Control Systems
by: Ruiter, Marijn, et al.
Published: (2026)

Neural-Rendezvous: Provably Robust Guidance and Control to Encounter Interstellar Objects
by: Tsukamoto, Hiroyasu, et al.
Published: (2022)

ShieldNN: A Provably Safe NN Filter for Unsafe NN Controllers
by: Ferlez, James, et al.
Published: (2020)

Parameter-Adaptive Approximate MPC: Tuning Neural-Network Controllers without Retraining
by: Hose, Henrik, et al.
Published: (2024)

Sample-Free Safety Assessment of Neural Network Controllers via Taylor Methods
by: Evans, Adam, et al.
Published: (2026)

Physics-Informed Graph Neural Network for Dynamic Reconfiguration of Power Systems
by: Authier, Jules, et al.
Published: (2023)

Incremental Correction in Dynamic Systems Modelled with Neural Networks for Constraint Satisfaction
by: Cho, Namhoon, et al.
Published: (2022)

Negative Imaginary Neural ODEs: Learning to Control Mechanical Systems with Stability Guarantees
by: Shi, Kanghong, et al.
Published: (2025)

Predictor-Based Output-Feedback Control of Linear Systems with Time-Varying Input and Measurement Delays via Neural-Approximated Prediction Horizons
by: Bhan, Luke, et al.
Published: (2026)

Reinforcement Learning-based Control via Y-wise Affine Neural Networks (YANNs)
by: Braniff, Austin, et al.
Published: (2025)

On the Stability of Nonlinear Receding Horizon Control: A Geometric Perspective
by: Westenbroek, Tyler, et al.
Published: (2021)

Control Occupation Kernel Regression for Nonlinear Control-Affine Systems
by: Abudia, Moad, et al.
Published: (2021)

A Framework for Adaptive Stabilisation of Nonlinear Stochastic Systems
by: Siriya, Seth, et al.
Published: (2025)

ReLU Networks for Model Predictive Control: Network Complexity and Performance Guarantees
by: Li, Xingchen, et al.
Published: (2026)

Provably Safe Control for Constrained Nonlinear Systems with Bounded Input
by: Kumar, Saurabh, et al.
Published: (2025)

Meta-Learning for Physically-Constrained Neural System Identification
by: Chakrabarty, Ankush, et al.
Published: (2025)

Safe and Robust Domains of Attraction for Discrete-Time Systems: A Set-Based Characterization and Certifiable Neural Network Estimation
by: Serry, Mohamed, et al.
Published: (2026)

Estimation Sample Complexity of a Class of Nonlinear Continuous-time Systems
by: Kuang, Simon, et al.
Published: (2023)

Learning-Based Optimal Control with Performance Guarantees for Unknown Systems with Latent States
by: Lefringhausen, Robert, et al.
Published: (2023)

Reinforcement Learning-based Control via Y-wise Affine Neural Networks: Comparative Case Studies for Chemical Processes
by: Braniff, Austin, et al.
Published: (2026)

Non-Asymptotic Bounds for Closed-Loop Identification of Unstable Nonlinear Stochastic Systems
by: Siriya, Seth, et al.
Published: (2024)

Lotka-Sharpe Neural Operators for Control of Population PDEs
by: Krstic, Miroslav, et al.
Published: (2026)

Drift Control of High-Dimensional RBM: A Computational Method Based on Neural Networks
by: Ata, Baris, et al.
Published: (2023)

Certified Robust Invariant Polytope Training in Neural Controlled ODEs
by: Harapanahalli, Akash, et al.
Published: (2024)

Formally Verified Physics-Informed Neural Control Lyapunov Functions
by: Liu, Jun, et al.
Published: (2024)