Incremental Correction in Dynamic Systems Modelled with Neural Networks for Constraint Satisfaction
Fuente:
arXiv
Saved in:
| Main Authors: | Cho, Namhoon, Shin, Hyo-Sang, Tsourdos, Antonios, Amato, Davide |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Passivity-Based Method for Accelerated Convex Optimisation
by: Cho, Namhoon, et al.
Published: (2023)
by: Cho, Namhoon, et al.
Published: (2023)
Optimisation of Structured Neural Controller Based on Continuous-Time Policy Gradient
by: Cho, Namhoon, et al.
Published: (2022)
by: Cho, Namhoon, et al.
Published: (2022)
Synchronisation-Oriented Design Approach for Adaptive Control
by: Cho, Namhoon, et al.
Published: (2024)
by: Cho, Namhoon, et al.
Published: (2024)
A Domain-Knowledge-Aided Deep Reinforcement Learning Approach for Flight Control Design
by: Shin, Hyo-Sang, et al.
Published: (2019)
by: Shin, Hyo-Sang, et al.
Published: (2019)
Predictive & Trust-based Multi-Agent Coordination
by: Renganathan, Venkatraman, et al.
Published: (2025)
by: Renganathan, Venkatraman, et al.
Published: (2025)
Physics-Informed Graph Neural Network for Dynamic Reconfiguration of Power Systems
by: Authier, Jules, et al.
Published: (2023)
by: Authier, Jules, et al.
Published: (2023)
On Constraints in First-Order Optimization: A View from Non-Smooth Dynamical Systems
by: Muehlebach, Michael, et al.
Published: (2021)
by: Muehlebach, Michael, et al.
Published: (2021)
Forward Invariance in Neural Network Controlled Systems
by: Harapanahalli, Akash, et al.
Published: (2023)
by: Harapanahalli, Akash, et al.
Published: (2023)
System-level Safety Guard: Safe Tracking Control through Uncertain Neural Network Dynamics Models
by: Li, Xiao, et al.
Published: (2023)
by: Li, Xiao, et al.
Published: (2023)
Learning Dissipative Neural Dynamical Systems
by: Xu, Yuezhu, et al.
Published: (2023)
by: Xu, Yuezhu, et al.
Published: (2023)
Distributed Control of Network Systems in the Space of Stabilizing Graph Neural Network Policies
by: Cao, John, et al.
Published: (2025)
by: Cao, John, et al.
Published: (2025)
Provably-Stable Neural Network-Based Control of Nonlinear Systems
by: Li, Anran, et al.
Published: (2025)
by: Li, Anran, et al.
Published: (2025)
Neural Contraction Metrics with Formal Guarantees for Discrete-Time Nonlinear Dynamical Systems
by: Li, Haoyu, et al.
Published: (2025)
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)
by: Harapanahalli, Akash, et al.
Published: (2023)
Near-Optimal Distributed Linear-Quadratic Regulator for Networked Systems
by: Shin, Sungho, et al.
Published: (2022)
by: Shin, Sungho, et al.
Published: (2022)
Neural Network-assisted Interval Reachability for Systems with Control Barrier Function-Based Safe Controllers
by: Ajeyemi, Damola, et al.
Published: (2025)
by: Ajeyemi, Damola, 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)
by: Wei, Lai, et al.
Published: (2021)
Joint Learning of Linear Dynamical Systems under Smoothness Constraints
by: Tyagi, Hemant
Published: (2024)
by: Tyagi, Hemant
Published: (2024)
Improved Scalable Lipschitz Bounds for Deep Neural Networks
by: Syed, Usman, et al.
Published: (2025)
by: Syed, Usman, et al.
Published: (2025)
Dynamic Deep-Reinforcement-Learning Algorithm in Partially Observable Markov Decision Processes
by: Omi, Saki, et al.
Published: (2023)
by: Omi, Saki, et al.
Published: (2023)
Meta-Learning for Physically-Constrained Neural System Identification
by: Chakrabarty, Ankush, et al.
Published: (2025)
by: Chakrabarty, Ankush, et al.
Published: (2025)
RHYME-XT: A Neural Operator for Spatiotemporal Control Systems
by: Ruiter, Marijn, et al.
Published: (2026)
by: Ruiter, Marijn, et al.
Published: (2026)
Efficient Interaction-Aware Interval Analysis of Neural Network Feedback Loops
by: Jafarpour, Saber, et al.
Published: (2023)
by: Jafarpour, Saber, et al.
Published: (2023)
Efficient Reachability Analysis for Convolutional Neural Networks Using Hybrid Zonotopes
by: Zhang, Yuhao, et al.
Published: (2025)
by: Zhang, Yuhao, et al.
Published: (2025)
A New Approach to Controlling Linear Dynamical Systems
by: Brahmbhatt, Anand, et al.
Published: (2025)
by: Brahmbhatt, Anand, et al.
Published: (2025)
Physics-Informed Neural Network Lyapunov Functions: PDE Characterization, Learning, and Verification
by: Liu, Jun, et al.
Published: (2023)
by: Liu, Jun, et al.
Published: (2023)
Stability and Performance Analysis of Discrete-Time ReLU Recurrent Neural Networks
by: Noori, Sahel Vahedi, et al.
Published: (2024)
by: Noori, Sahel Vahedi, et al.
Published: (2024)
Parameter-Adaptive Approximate MPC: Tuning Neural-Network Controllers without Retraining
by: Hose, Henrik, et al.
Published: (2024)
by: Hose, Henrik, et al.
Published: (2024)
Fast and Reliable $N-k$ Contingency Screening with Input-Convex Neural Networks
by: Christianson, Nicolas, et al.
Published: (2024)
by: Christianson, Nicolas, et al.
Published: (2024)
Sample-Free Safety Assessment of Neural Network Controllers via Taylor Methods
by: Evans, Adam, et al.
Published: (2026)
by: Evans, Adam, et al.
Published: (2026)
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)
by: Serry, Mohamed, et al.
Published: (2026)
Symmetric Linear Dynamical Systems are Learnable from Few Observations
by: Vu, Minh, et al.
Published: (2025)
by: Vu, Minh, et al.
Published: (2025)
Efficient Spectral Control of Partially Observed Linear Dynamical Systems
by: Brahmbhatt, Anand, et al.
Published: (2025)
by: Brahmbhatt, Anand, et al.
Published: (2025)
Finite Sample Identification of Partially Observed Bilinear Dynamical Systems
by: Sattar, Yahya, et al.
Published: (2025)
by: Sattar, Yahya, et al.
Published: (2025)
Negative Imaginary Neural ODEs: Learning to Control Mechanical Systems with Stability Guarantees
by: Shi, Kanghong, et al.
Published: (2025)
by: Shi, Kanghong, et al.
Published: (2025)
Reinforcement Learning-based Control via Y-wise Affine Neural Networks (YANNs)
by: Braniff, Austin, et al.
Published: (2025)
by: Braniff, Austin, et al.
Published: (2025)
Universal Approximation Power of Deep Residual Neural Networks via Nonlinear Control Theory
by: Tabuada, Paulo, et al.
Published: (2020)
by: Tabuada, Paulo, et al.
Published: (2020)
Safely Learning Dynamical Systems
by: Ahmadi, Amir Ali, et al.
Published: (2023)
by: Ahmadi, Amir Ali, et al.
Published: (2023)
A Nonlinear Separation Principle via Contraction Theory: Applications to Neural Networks, Control, and Learning
by: Gokhale, Anand, et al.
Published: (2026)
by: Gokhale, Anand, et al.
Published: (2026)
Critical Influence of Overparameterization on Sharpness-aware Minimization
by: Shin, Sungbin, et al.
Published: (2023)
by: Shin, Sungbin, et al.
Published: (2023)
Similar Items
-
A Passivity-Based Method for Accelerated Convex Optimisation
by: Cho, Namhoon, et al.
Published: (2023) -
Optimisation of Structured Neural Controller Based on Continuous-Time Policy Gradient
by: Cho, Namhoon, et al.
Published: (2022) -
Synchronisation-Oriented Design Approach for Adaptive Control
by: Cho, Namhoon, et al.
Published: (2024) -
A Domain-Knowledge-Aided Deep Reinforcement Learning Approach for Flight Control Design
by: Shin, Hyo-Sang, et al.
Published: (2019) -
Predictive & Trust-based Multi-Agent Coordination
by: Renganathan, Venkatraman, et al.
Published: (2025)