Imagen de Portada

Suppressing unknown disturbances to dynamical systems using machine learning

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Restrepo, Juan G., Byers, Clayton P., Skardal, Per Sebastian
Formato:	Preprint
Publicado:	2023
Materias:	Systems and Control Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Suboptimality analysis of receding horizon quadratic control with unknown linear systems and its applications in learning-based control
por: Shi, Shengling, et al.
Publicado: (2023)

Recommender systems and reinforcement learning for human-building interaction and context-aware support: A text mining-driven review of scientific literature
por: Zhang, Wenhao, et al.
Publicado: (2024)

Driving behavior-guided battery health monitoring for electric vehicles using machine learning
por: Jiang, Nanhua, et al.
Publicado: (2023)

Stabilization of nonlinear systems with unknown delays via delay-adaptive neural operator approximate predictors
por: Bhan, Luke, et al.
Publicado: (2025)

Macroscopic dynamics of oscillator ensembles with communities, higher-order interactions, and phase lags
por: Adhikari, Sabina, et al.
Publicado: (2025)

Stabilization of industrial processes with time series machine learning
por: Anoshin, Matvei, et al.
Publicado: (2025)

Revealing design archetypes and flexibility in e-molecule import pathways using Modeling to Generate Alternatives and interpretable machine learning
por: Kchaou, Mahdi, et al.
Publicado: (2025)

Creating synthetic energy meter data using conditional diffusion and building metadata
por: Fu, Chun, et al.
Publicado: (2024)

On zero-shot learning in neural state estimation of power distribution systems
por: Berezin, Aleksandr, et al.
Publicado: (2024)

Unsupervised machine learning for data-driven rock mass classification: addressing limitations in existing systems using drilling data
por: Hansen, T. F., et al.
Publicado: (2024)

Interpretable machine-learning for predicting molecular weight of PLA based on artificial bee colony optimization algorithm and adaptive neurofuzzy inference system
por: Masoumi, Amir Pouya, et al.
Publicado: (2025)

Accelerating process control and optimization via machine learning: A review
por: Mitrai, Ilias, et al.
Publicado: (2024)

Enhanced Transformer architecture for in-context learning of dynamical systems
por: Rufolo, Matteo, et al.
Publicado: (2024)

Domain knowledge-guided machine learning framework for state of health estimation in Lithium-ion batteries
por: Lanubile, Andrea, et al.
Publicado: (2024)

Learning mechanical systems from real-world data using discrete forced Lagrangian dynamics
por: Hansen, Martine Dyring, et al.
Publicado: (2025)

The interplay of robustness and generalization in quantum machine learning
por: Berberich, Julian, et al.
Publicado: (2025)

Symmetric Hermite quadrature-based balanced truncation for learning linear dynamical systems from derivative data
por: Reiter, Sean, et al.
Publicado: (2026)

Control of dynamical systems with neural networks
por: Böttcher, Lucas
Publicado: (2025)

Shape error prediction in 5-axis machining using graph neural networks
por: Huuk, Julia, et al.
Publicado: (2024)

Manifold meta-learning for reduced-complexity neural system identification
por: Forgione, Marco, et al.
Publicado: (2025)

Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method
por: Caldarelli, Edoardo, et al.
Publicado: (2024)

Tracking control of latent dynamic systems with application to spacecraft attitude control
por: Zhang, Congxi, et al.
Publicado: (2024)

Tensor-based process control and monitoring for semiconductor manufacturing with unstable disturbances
por: Li, Yanrong, et al.
Publicado: (2024)

A modular framework for stabilizing deep reinforcement learning control
por: Lawrence, Nathan P., et al.
Publicado: (2023)

GreenLight-Gym: Reinforcement learning benchmark environment for control of greenhouse production systems
por: van Laatum, Bart, et al.
Publicado: (2024)

Coupled autoregressive active inference agents for control of multi-joint dynamical systems
por: Nisslbeck, Tim N., et al.
Publicado: (2024)

Unsupervised clustering of disturbances in power systems via deep convolutional autoencoders
por: Islam, Md Maidul, et al.
Publicado: (2023)

Machine learning based state observer for discrete time systems evolving on Lie groups
por: Shanbhag, Soham, et al.
Publicado: (2024)

What can we learn from signals and systems in a transformer? Insights for probabilistic modeling and inference architecture
por: Chang, Heng-Sheng, et al.
Publicado: (2025)

Exploiting inter-agent coupling information for efficient reinforcement learning of cooperative LQR
por: Syed, Shahbaz P Qadri, et al.
Publicado: (2025)

Operator learning for energy-efficient building ventilation control with computational fluid dynamics simulation of a real-world classroom
por: Bian, Yuexin, et al.
Publicado: (2025)

Independent policy gradient-based reinforcement learning for economic and reliable energy management of multi-microgrid systems
por: Hu, Junkai, et al.
Publicado: (2025)

SafEDMD: A Koopman-based data-driven controller design framework for nonlinear dynamical systems
por: Strässer, Robin, et al.
Publicado: (2024)

Structured state-space models are deep Wiener models
por: Bonassi, Fabio, et al.
Publicado: (2023)

Model-free system identification of surface ships in waves via Hankel dynamic mode decomposition with control
por: Palma, Giorgio, et al.
Publicado: (2025)

MPCritic: A plug-and-play MPC architecture for reinforcement learning
por: Lawrence, Nathan P., et al.
Publicado: (2025)

Learning to optimize with convergence guarantees using nonlinear system theory
por: Martin, Andrea, et al.
Publicado: (2024)

FNO$^{\angle θ}$: Extended Fourier neural operator for learning state and optimal control of distributed parameter systems
por: Li, Zhexian, et al.
Publicado: (2026)

Digital twin with automatic disturbance detection for real-time optimization of a semi-autogenous grinding (SAG) mill
por: Quintanilla, Paulina, et al.
Publicado: (2024)

Direct transfer of optimized controllers to similar systems using dimensionless MPC
por: Hromatko, Josip Kir, et al.
Publicado: (2025)