Physics-guided gated recurrent units for inversion-based feedforward control
Fuente:
arXiv
Saved in:
| Main Authors: | Lin, Mingdao, Bolderman, Max, Lazar, Mircea |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Physics-guided neural networks for inversion-based feedforward control applied to hybrid stepper motors
by: Fan, Daiwei, et al.
Published: (2023)
by: Fan, Daiwei, et al.
Published: (2023)
Data-driven feedforward control design for nonlinear systems: A control-oriented system identification approach
by: Bolderman, Max, et al.
Published: (2023)
by: Bolderman, Max, et al.
Published: (2023)
Physics-guided neural networks for feedforward control with input-to-state stability guarantees
by: Bolderman, Max, et al.
Published: (2023)
by: Bolderman, Max, et al.
Published: (2023)
Structured physics-guided neural networks for electromagnetic commutation applied to industrial linear motors
by: Bolderman, Max, et al.
Published: (2024)
by: Bolderman, Max, et al.
Published: (2024)
A universal reproducing kernel Hilbert space for learning nonlinear systems operators
by: Lazar, Mircea
Published: (2024)
by: Lazar, Mircea
Published: (2024)
Neural Data-Enabled Predictive Control
by: Lazar, Mircea
Published: (2024)
by: Lazar, Mircea
Published: (2024)
Kernelized offset-free data-driven predictive control for nonlinear systems
by: de Jong, Thomas Oliver, et al.
Published: (2024)
by: de Jong, Thomas Oliver, et al.
Published: (2024)
Finite Control Set Model Predictive Control with Limit Cycle Stability Guarantees
by: Xu, Duo, et al.
Published: (2024)
by: Xu, Duo, et al.
Published: (2024)
Dynamic Output-Feedback Controller Synthesis for Dissipativity and $H_2$ Performance from Noisy Input-State Data
by: Kristović, Pietro, et al.
Published: (2025)
by: Kristović, Pietro, et al.
Published: (2025)
Dynamic Output-Feedback Controller Synthesis for Dissipativity and $H_2$ Performance from Noisy Input-Output Data
by: Kristović, Pietro, et al.
Published: (2026)
by: Kristović, Pietro, et al.
Published: (2026)
Multivariable control of modular multilevel converters with convergence and safety guarantees
by: Dreke, Victor Daniel Reyes, et al.
Published: (2024)
by: Dreke, Victor Daniel Reyes, et al.
Published: (2024)
Offset-free Data-Driven Predictive Control for Grid-Connected Power Converters in Weak Grid Faults
by: Kraayeveld, Ivo, et al.
Published: (2025)
by: Kraayeveld, Ivo, et al.
Published: (2025)
Neural Parameter-varying Data-enabled Predictive Control of Cold Atmospheric Pressure Plasma Jets
by: GhafGhanbari, Pegah, et al.
Published: (2025)
by: GhafGhanbari, Pegah, et al.
Published: (2025)
Robust direct acoustic impedance control using two microphones for mixed feedforward-feedback controller
by: Volery, Maxime, et al.
Published: (2021)
by: Volery, Maxime, et al.
Published: (2021)
State of health prediction of lithium-ion batteries for driving conditions based on full parameter domain sparrow search algorithm and dual-module bidirectional gated recurrent unit
by: Wen, Jie, et al.
Published: (2025)
by: Wen, Jie, et al.
Published: (2025)
Koopman Data-Driven Predictive Control with Robust Stability and Recursive Feasibility Guarantees
by: de Jong, Thomas, et al.
Published: (2024)
by: de Jong, Thomas, et al.
Published: (2024)
Scalable Nonlinear DeePC: Bridging Direct and Indirect Methods and Basis Reduction
by: de Jong, Thomas O., et al.
Published: (2025)
by: de Jong, Thomas O., et al.
Published: (2025)
Situation-Aware Interactive MPC Switching for Autonomous Driving
by: Qi, Shuhao, et al.
Published: (2025)
by: Qi, Shuhao, et al.
Published: (2025)
When is cumulative dose response monotonic? Analysis of incoherent feedforward motifs
by: Wafi, Moh Kamalul, et al.
Published: (2026)
by: Wafi, Moh Kamalul, et al.
Published: (2026)
Stochastic MPC for Finite Gaussian Mixture Disturbances with Guarantees
by: Engelaar, Maico H. W., et al.
Published: (2024)
by: Engelaar, Maico H. W., et al.
Published: (2024)
Regional stability conditions for recurrent neural network-based control systems
by: La Bella, Alessio, et al.
Published: (2024)
by: La Bella, Alessio, et al.
Published: (2024)
Feedback-feedforward Signal Control with Exogenous Demand Estimation in Congested Urban Road Networks
by: Pedroso, Leonardo, et al.
Published: (2023)
by: Pedroso, Leonardo, et al.
Published: (2023)
Risk-Aware MPC for Stochastic Systems with Runtime Temporal Logics
by: Engelaar, Maico H. W., et al.
Published: (2024)
by: Engelaar, Maico H. W., et al.
Published: (2024)
From Product Hilbert Spaces to the Generalized Koopman Operator and the Nonlinear Fundamental Lemma
by: Lazar, Mircea
Published: (2025)
by: Lazar, Mircea
Published: (2025)
Risk-Aware Real-Time Task Allocation for Stochastic Multi-Agent Systems under STL Specifications
by: Engelaar, Maico H. W., et al.
Published: (2024)
by: Engelaar, Maico H. W., et al.
Published: (2024)
Multi-gated perimeter flow control for monocentric cities: Efficiency and equity
by: Jusoh, Ruzanna Mat, et al.
Published: (2024)
by: Jusoh, Ruzanna Mat, et al.
Published: (2024)
Efficient sparse GP-MPC with accurate mean and variance propagation applied for quadcopter flight control
by: Badakis, Giannis, et al.
Published: (2026)
by: Badakis, Giannis, et al.
Published: (2026)
Learning-to-solve unit commitment based on few-shot physics-guided spatial-temporal graph convolution network
by: Yang, Mei, et al.
Published: (2024)
by: Yang, Mei, et al.
Published: (2024)
Projection-based discrete-time consensus on the unit sphere
by: Thunberg, Johan, et al.
Published: (2026)
by: Thunberg, Johan, et al.
Published: (2026)
Data-driven model predictive control of battery storage units
by: Lipka, Johannes B., et al.
Published: (2024)
by: Lipka, Johannes B., et al.
Published: (2024)
eXplainable AI for data driven control: an inverse optimal control approach
by: Porcari, Federico, et al.
Published: (2025)
by: Porcari, Federico, et al.
Published: (2025)
Goal-oriented safe active learning for predictive control using Bayesian recurrent neural networks
by: de Giuli, Laura Boca, et al.
Published: (2026)
by: de Giuli, Laura Boca, et al.
Published: (2026)
Counter-example guided inductive synthesis of control Lyapunov functions for uncertain systems
by: Masti, Daniele, et al.
Published: (2023)
by: Masti, Daniele, et al.
Published: (2023)
Physics-informed structured learning of a class of recurrent neural networks with guaranteed properties
by: Ravasio, Daniele, et al.
Published: (2026)
by: Ravasio, Daniele, et al.
Published: (2026)
Decentralized Contingency MPC based on Safe Sets for Nonlinear Multi-agent Collision Avoidance
by: Studt, Max, et al.
Published: (2026)
by: Studt, Max, et al.
Published: (2026)
Statistically consistent inverse optimal control for discrete-time indefinite linear-quadratic systems
by: Zhang, Han, et al.
Published: (2022)
by: Zhang, Han, et al.
Published: (2022)
Imitation learning with artificial neural networks for demand response with a heuristic control approach for heat pumps
by: Dengiz, Thomas, et al.
Published: (2024)
by: Dengiz, Thomas, et al.
Published: (2024)
Microwave-acoustic-based isolated gate driver for power electronics
by: Jin, Liyang, et al.
Published: (2025)
by: Jin, Liyang, et al.
Published: (2025)
Specification-guided temporal logic control for stochastic systems: a multi-layered approach
by: van Huijgevoort, Birgit C., et al.
Published: (2024)
by: van Huijgevoort, Birgit C., et al.
Published: (2024)
Vector-field guided constraint-following control for path following of uncertain mechanical systems
by: Yin, Hui, et al.
Published: (2026)
by: Yin, Hui, et al.
Published: (2026)
Similar Items
-
Physics-guided neural networks for inversion-based feedforward control applied to hybrid stepper motors
by: Fan, Daiwei, et al.
Published: (2023) -
Data-driven feedforward control design for nonlinear systems: A control-oriented system identification approach
by: Bolderman, Max, et al.
Published: (2023) -
Physics-guided neural networks for feedforward control with input-to-state stability guarantees
by: Bolderman, Max, et al.
Published: (2023) -
Structured physics-guided neural networks for electromagnetic commutation applied to industrial linear motors
by: Bolderman, Max, et al.
Published: (2024) -
A universal reproducing kernel Hilbert space for learning nonlinear systems operators
by: Lazar, Mircea
Published: (2024)