Cover Image

A Digital Twin Framework for Generation-IV Reactors with Reinforcement Learning-Enabled Health-Aware Supervisory Control

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lim, Jasmin Y., Pylorof, Dimitrios, Garcia, Humberto E., Duraisamy, Karthik
Format:	Preprint
Published:	2025
Subjects:	Systems and Control Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Online Learning for Supervisory Switching Control
by: Sun, Haoyuan, et al.
Published: (2026)

A Safe Reinforcement Learning Algorithm for Supervisory Control of Power Plants
by: Sun, Yixuan, et al.
Published: (2024)

An AI-Driven Thermal-Fluid Testbed for Advanced Small Modular Reactors: Integration of Digital Twin and Large Language Models
by: Lim, Doyeong, et al.
Published: (2025)

Data-driven Supervisory Control under Attacks via Spectral Learning
by: Smith, Nathaniel, et al.
Published: (2025)

Control-Certified Wireless Resource Allocation for Digital-Twin-Enabled UAV Swarms
by: Luo, Qingyun, et al.
Published: (2026)

Digital Twin of Autonomous Surface Vessels for Safe Maritime Navigation Enabled through Predictive Modeling and Reinforcement Learning
by: Menges, Daniel, et al.
Published: (2024)

A Digital Twin Framework for Reinforcement Learning with Real-Time Self-Improvement via Human Assistive Teleoperation
by: Olayemi, Kabirat, et al.
Published: (2024)

Uncertainty-Aware Digital Twins: Robust Model Predictive Control using Time-Series Deep Quantile Learning
by: Chen, Yi-Ping, et al.
Published: (2025)

Surrogate Modeling and Control of Medical Digital Twins
by: Fonseca, Luis L., et al.
Published: (2024)

Opacity Enforcing Supervisory Control with a Priori Unknown Supervisors
by: Cui, Bohan, et al.
Published: (2026)

Failsafe Mechanism Design of Multicopters Based on Supervisory Control Theory
by: Quan, Quan, et al.
Published: (2017)

Control Affine Hybrid Power Plant Subsystem Modeling for Supervisory Control Design
by: Ampleman, Stephen, et al.
Published: (2025)

A Novel Approach to Grasping Control of Soft Robotic Grippers based on Digital Twin
by: Xiang, Tianyi, et al.
Published: (2024)

Bounded-Time Nonblocking Supervisory Control of Timed Discrete-Event Systems
by: Zhang, Renyuan, et al.
Published: (2024)

Identification of Minimally Restrictive Assembly Sequences using Supervisory Control Theory
by: Vinetti, Martina, et al.
Published: (2025)

Optimizing Reinforcement Learning Training over Digital Twin Enabled Multi-fidelity Networks
by: Yu, Hanzhi, et al.
Published: (2026)

Overview of Controllability Definitions in Supervisory Control Theory
by: Keiren, Jeroen J. A., et al.
Published: (2025)

Supervisory Control Theory with Event Forcing
by: Reniers, Michel, et al.
Published: (2024)

Digital Twin-Driven Reinforcement Learning for Obstacle Avoidance in Robot Manipulators: A Self-Improving Online Training Framework
by: Sun, Yuzhu, et al.
Published: (2024)

RoboTwin: A Robotic Teleoperation Framework Using Digital Twins
by: Yelchuri, Harsha, et al.
Published: (2025)

Extracting Koopman Operators for Prediction and Control of Non-linear Dynamics Using Two-stage Learning and Oblique Projections
by: Uchida, Daisuke, et al.
Published: (2023)

Supervisory Control of Discrete Event Systems for Small Language Under Cyber Attacks
by: Wang, Xiaojun, et al.
Published: (2025)

Digital Twin Assisted Deep Reinforcement Learning for Online Admission Control in Sliced Network
by: Tao, Zhenyu, et al.
Published: (2023)

Mobile Edge Generation-Enabled Digital Twin: Architecture Design and Research Opportunities
by: Xu, Xiaoxia, et al.
Published: (2024)

Executor-Side Progressive Risk-Gated Actuation for Agentic AI in Wireless Supervisory Control
by: Liu, Zhenyu, et al.
Published: (2026)

Control of Medical Digital Twins with Artificial Neural Networks
by: Böttcher, Lucas, et al.
Published: (2024)

Digital Twin-based Cooperative Autonomous Driving in Smart Intersections: A Multi-Agent Reinforcement Learning Approach
by: Yu, Taoyuan, et al.
Published: (2025)

Sustainability of Data Center Digital Twins with Reinforcement Learning
by: Sarkar, Soumyendu, et al.
Published: (2024)

Guided Bayesian Optimization: Data-Efficient Controller Tuning with Digital Twin
by: Nobar, Mahdi, et al.
Published: (2024)

Model Predictive Control of Nonlinear Dynamics Using Online Adaptive Koopman Operators
by: Uchida, Daisuke, et al.
Published: (2024)

Data-driven Koopman Operator-based Prediction and Control Using Model Averaging
by: Uchida, Daisuke, et al.
Published: (2024)

Foundation Twins: A New Generation of Power Systems Digital Twins using Foundation AI Models
by: Vergara, Pedro P.
Published: (2026)

A Game-Theoretical Approach for Optimal Supervisory Control of Discrete Event Systems under Energy Constraints
by: Lv, Peng, et al.
Published: (2024)

A Linear Test for Global Nonlinear Controllability
by: Elamvazhuthi, Karthik
Published: (2024)

Digital Twin-Enabled Blockage-Aware Dynamic mmWave Multi-Hop V2X Communication
by: Roongpraiwan, Supat, et al.
Published: (2025)

Markov Clustering based Fully Automated Nonblocking Hierarchical Supervisory Control of Large-Scale Discrete-Event Systems
by: Liu, Yingying, et al.
Published: (2025)

Prescribing Optimal Health-Aware Operation for Urban Air Mobility with Deep Reinforcement Learning
by: Montazeri, Mina, et al.
Published: (2024)

A Framework for Scalable Digital Twin Deployment in Smart Campus Building Facility Management
by: Siv, Thyda
Published: (2025)

Digital Twin of Aerosol Jet Printing
by: Agarwal, Aayushya, et al.
Published: (2025)

Physics-Informed Unit Commitment Framework for Nuclear Reactors
by: Choudhury, Shiny, et al.
Published: (2025)