Image de couverture de livre

Data-Driven Adaptive PID Control Based on Physics-Informed Neural Networks

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Ito, Junsei, Wasa, Yasuaki
Format:	Preprint
Publié:	2025
Sujets:	Systems and Control Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Model Predictive Path Integral PID Control for Learning-Based Path Following
par: Kato, Teruki, et autres
Publié: (2026)

Adaptive Model-Predictive Control of a Soft Continuum Robot Using a Physics-Informed Neural Network Based on Cosserat Rod Theory
par: Licher, Johann, et autres
Publié: (2025)

Formally Verified Physics-Informed Neural Control Lyapunov Functions
par: Liu, Jun, et autres
Publié: (2024)

A Physics-Informed Neural Networks-Based Model Predictive Control Framework for $SIR$ Epidemics
par: Zhong, Aiping, et autres
Publié: (2025)

Bayesian Physics Informed Neural Networks for Reliable Transformer Prognostics
par: Ramirez, Ibai, et autres
Publié: (2025)

Scalable Physics-Informed Neural Differential Equations and Data-Driven Algorithms for HVAC Systems
par: Zhai, Hanfeng, et autres
Publié: (2026)

RobustNeuralNetworks.jl: a Package for Machine Learning and Data-Driven Control with Certified Robustness
par: Barbara, Nicholas H., et autres
Publié: (2023)

Physics-Informed Graph Neural Network for Dynamic Reconfiguration of Power Systems
par: Authier, Jules, et autres
Publié: (2023)

Physics-Informed Neural Networks for Accelerating Power System State Estimation
par: Falas, Solon, et autres
Publié: (2023)

Physics-Informed Heterogeneous Graph Neural Networks for DC Blocker Placement
par: Jin, Hongwei, et autres
Publié: (2024)

Physics-Informed Neural Network Lyapunov Functions: PDE Characterization, Learning, and Verification
par: Liu, Jun, et autres
Publié: (2023)

Optimal Sensor Placement in Power Transformers Using Physics-Informed Neural Networks
par: Li, Sirui, et autres
Publié: (2025)

Robust Power System State Estimation using Physics-Informed Neural Networks
par: Falas, Solon, et autres
Publié: (2025)

Parameter-Adaptive Approximate MPC: Tuning Neural-Network Controllers without Retraining
par: Hose, Henrik, et autres
Publié: (2024)

Contraction-Guided Adaptive Partitioning for Reachability Analysis of Neural Network Controlled Systems
par: Harapanahalli, Akash, et autres
Publié: (2023)

Provably-Stable Neural Network-Based Control of Nonlinear Systems
par: Li, Anran, et autres
Publié: (2025)

Verifiable Error Bounds for Physics-Informed Neural Network Solutions of Lyapunov and Hamilton-Jacobi-Bellman Equations
par: Liu, Jun
Publié: (2026)

Neural Network-assisted Interval Reachability for Systems with Control Barrier Function-Based Safe Controllers
par: Ajeyemi, Damola, et autres
Publié: (2025)

Physics-Informed Deep B-Spline Networks
par: Wang, Zhuoyuan, et autres
Publié: (2025)

Usage-Specific Survival Modeling Based on Operational Data and Neural Networks
par: Holmer, Olov, et autres
Publié: (2024)

Verifiable Error Bounds for Physics-Informed Neural KKL Observers
par: Berin-Costain, Hannah, et autres
Publié: (2026)

Adaptive Path Integral Diffusion: AdaPID
par: Chertkov, Michael, et autres
Publié: (2025)

Symptom-Driven Personalized Proton Pump Inhibitors Therapy Using Bayesian Neural Networks and Model Predictive Control
par: Li, Yutong, et autres
Publié: (2025)

Autonomous Vehicle Lateral Control Using Deep Reinforcement Learning with MPC-PID Demonstration
par: Wu, Chengdong, et autres
Publié: (2025)

Online Control of Linear Systems under Unbounded Noise
par: Ito, Kaito, et autres
Publié: (2024)

Learning Transferable Friction Models and LuGre Identification Via Physics-Informed Neural Networks
par: Ozmen, Asutay, et autres
Publié: (2025)

Forward Invariance in Neural Network Controlled Systems
par: Harapanahalli, Akash, et autres
Publié: (2023)

A Digital Twin for Diesel Engines: Operator-infused Physics-Informed Neural Networks with Transfer Learning for Engine Health Monitoring
par: Nath, Kamaljyoti, et autres
Publié: (2024)

Graph Neural Network-Based Distributed Optimal Control for Linear Networked Systems: An Online Distributed Training Approach
par: Song, Zihao, et autres
Publié: (2025)

Pontryagin Optimal Control via Neural Networks
par: Gu, Chengyang, et autres
Publié: (2022)

Data-Driven Adversarial Online Control for Unknown Linear Systems
par: Liu, Zishun, et autres
Publié: (2023)

Component-Aware Pruning Framework for Neural Network Controllers via Gradient-Based Importance Estimation
par: Sundaram, Ganesh, et autres
Publié: (2026)

PID Accelerated Temporal Difference Algorithms
par: Bedaywi, Mark, et autres
Publié: (2024)

Data-Driven Stochastic Optimal Control in Reproducing Kernel Hilbert Spaces
par: Hoischen, Nicolas, et autres
Publié: (2024)

Physics Informed Reinforcement Learning with Gibbs Priors for Topology Control in Power Grids
par: Dogoulis, Pantelis, et autres
Publié: (2026)

Distributed Control of Network Systems in the Space of Stabilizing Graph Neural Network Policies
par: Cao, John, et autres
Publié: (2025)

FPGA-Based Neural Thrust Controller for UAVs
par: Azem, Sharif, et autres
Publié: (2024)

Inverse Modeling of Dielectric Response in Time Domain using Physics-Informed Neural Networks
par: Esenov, Emir, et autres
Publié: (2025)

PINNSim: A Simulator for Power System Dynamics based on Physics-Informed Neural Networks
par: Stiasny, Jochen, et autres
Publié: (2023)

Direct Data Driven Control Using Noisy Measurements
par: Esmzad, Ramin, et autres
Publié: (2025)