Imagen de Portada

Data driven feedback linearization of nonlinear control systems via Lie derivatives and stacked regression approach

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	K., Lakshmi Priya P., Schwung, Andreas
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Transfer learning of state-based potential games for process optimization in decentralized manufacturing systems
por: Yuwono, Steve, et al.
Publicado: (2024)

Time Series Compression using Quaternion Valued Neural Networks and Quaternion Backpropagation
por: Pöppelbaum, Johannes, et al.
Publicado: (2024)

Self-optimization in distributed manufacturing systems using Modular State-based Stackelberg Games
por: Yuwono, Steve, et al.
Publicado: (2024)

Stabilizing Multimodal Autoencoders: A Theoretical and Empirical Analysis of Fusion Strategies
por: Altinses, Diyar, et al.
Publicado: (2025)

Layer-Specific Lipschitz Modulation for Fault-Tolerant Multimodal Representation Learning
por: Altinses, Diyar, et al.
Publicado: (2026)

Introducing PetriRL: An Innovative Framework for JSSP Resolution Integrating Petri nets and Event-based Reinforcement Learning
por: Lassoued, Sofiene, et al.
Publicado: (2024)

Distributed Stackelberg Strategies in State-based Potential Games for Autonomous Decentralized Learning Manufacturing Systems
por: Yuwono, Steve, et al.
Publicado: (2024)

Gradient-based Learning in State-based Potential Games for Self-Learning Production Systems
por: Yuwono, Steve, et al.
Publicado: (2024)

Improving Quaternion Neural Networks with Quaternionic Activation Functions
por: Pöppelbaum, Johannes, et al.
Publicado: (2024)

Prior-Informed Neural Network Initialization: A Spectral Approach for Function Parameterizing Architectures
por: Torres, David Orlando Salazar, et al.
Publicado: (2026)

Predicting Wall Thickness Changes in Cold Forging Processes: An Integrated FEM and Neural Network approach
por: Ilic, Sasa, et al.
Publicado: (2024)

A flexible empirical Bayes approach to multiple linear regression and connections with penalized regression
por: Kim, Youngseok, et al.
Publicado: (2022)

Transfer learning for functional linear regression via control variates
por: Yang, Yuping, et al.
Publicado: (2026)

Anomaly Detection using Ensemble Classification and Evidence Theory
por: Arévalo, Fernando, et al.
Publicado: (2022)

Data-driven identification of nonlinear dynamical systems with LSTM autoencoders and Normalizing Flows
por: Rostamijavanani, Abdolvahhab, et al.
Publicado: (2025)

Dimension-free bounds in high-dimensional linear regression via error-in-operator approach
por: Noskov, Fedor, et al.
Publicado: (2025)

Information Fusion for Assistance Systems in Production Assessment
por: Arévalo, Fernando, et al.
Publicado: (2023)

Data-driven system identification using quadratic embeddings of nonlinear dynamics
por: Klus, Stefan, et al.
Publicado: (2025)

Meta-learning of shared linear representations beyond well-specified linear regression
por: Even, Mathieu, et al.
Publicado: (2025)

Data-driven model order reduction for structures with piecewise linear nonlinearity using dynamic mode decomposition
por: Saito, Akira, et al.
Publicado: (2026)

Augmented balancing weights as linear regression
por: Bruns-Smith, David, et al.
Publicado: (2023)

Semi-supervised learning for linear extremile regression
por: Jiang, Rong, et al.
Publicado: (2025)

Data/moment-driven approaches for fast predictive control of collective dynamics
por: Albi, Giacomo, et al.
Publicado: (2024)

Deep learning architectures for data-driven damage detection in nonlinear dynamic systems
por: Joseph, Harrish, et al.
Publicado: (2024)

Pragmatic auditing: a pilot-driven approach for auditing Machine Learning systems
por: Benbouzid, Djalel, et al.
Publicado: (2024)

Multifidelity Gaussian process regression for solving nonlinear partial differential equations
por: El-Boukkouri, Fatima-Zahrae, et al.
Publicado: (2026)

An L-BFGS-B approach for linear and nonlinear system identification under $\ell_1$ and group-Lasso regularization
por: Bemporad, Alberto
Publicado: (2024)

Comparing analytic and data-driven approaches to parameter identifiability: A power systems case study
por: Evangelou, Nikolaos, et al.
Publicado: (2024)

A variational Bayes approach to debiased inference for low-dimensional parameters in high-dimensional linear regression
por: Castillo, Ismaël, et al.
Publicado: (2024)

Deep linear networks for regression are implicitly regularized towards flat minima
por: Marion, Pierre, et al.
Publicado: (2024)

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

Improved Generation of Synthetic Imaging Data Using Feature-Aligned Diffusion
por: Nair, Lakshmi
Publicado: (2024)

Generalisation and benign over-fitting for linear regression onto random functional covariates
por: Jones, Andrew, et al.
Publicado: (2025)

Time-optimal neural feedback control of nilpotent systems as a binary classification problem
por: Bicego, Sara, et al.
Publicado: (2025)

Generative AI-driven forecasting of oil production
por: Gandhi, Yash, et al.
Publicado: (2024)

Closed-form congestion control via deep symbolic regression
por: Martins, Jean, et al.
Publicado: (2024)

Data-driven approaches to inverse problems
por: Schönlieb, Carola-Bibiane, et al.
Publicado: (2025)

Fast approximative estimation of conditional Shapley values when using a linear regression model or a polynomial regression model
por: Aanes, Fredrik Lohne
Publicado: (2025)

Non-parametric regression for robot learning on manifolds
por: Lopez-Custodio, P. C., et al.
Publicado: (2023)

Discovery and inference beyond linearity by integrating Bayesian regression, tree ensembles and Shapley values
por: Spadaccini, Giorgio, et al.
Publicado: (2025)