Latest Articles for Control Systems

New methods enhance control system performance amidst uncertainties.

Techniques for better control in electromechanical systems with weak connections.

Exploring methods to optimize control over quantum systems influenced by their environments.

Combining Hamilton-Jacobi reachability with reinforcement learning enhances safety in control systems.

New approaches enhance control strategies for complex, nonlinear systems using random features.

This article discusses methods to improve control systems using goal-oriented data compression.

New approaches in sliding mode control enhance stability and energy efficiency.

This article discusses a method for safe spacecraft docking in complex orbits.

New methods enhance stability and accuracy in complex matrix systems.

Researchers aim to improve control strategies using symmetries in various systems.

A new method enhances robot manipulation under uncertain conditions.

Study on optimizing particle behavior through control strategies in unpredictable environments.

Exploring methods for creating reliable controllers in various environments.

Using symmetry to enhance learning efficiency in aircraft control algorithms.

Learn how to tackle control systems with limited data using innovative methods.

This paper presents a new approach for efficient reachability analysis in complex control systems.

This article presents a method to enhance safety and stability in automation systems.

Learn how Markov Decision Processes improve decision-making in uncertain scenarios.

Evaluating MPC and RL for efficient battery control.

Neural networks are enhancing control systems for managing complex reaction-diffusion processes.

New frameworks for efficient modeling of complex networked systems in electrified vehicles.

Exploring deep Model Predictive Control for adaptable robotic movement.

Research shows how variability enhances ANN controllers for better performance in diverse environments.

A new approach improves state estimation amidst disturbances in nonlinear control systems.

A practical approach to model droop-controlled converters for better performance analysis.

A novel approach using deep reinforcement learning improves control of quantum systems.

Combining adaptive control with meta-learning improves system performance under uncertainty.

Introducing Closed-Loop Diffusion Control for efficient management of complex physical systems.

This article examines how RL helps control bicycles without additional support.

A look into performance-barrier event-triggered control in reaction-diffusion systems.

A new approach to improve coordination in layered control systems using reinforcement learning.

New methods enhance monitoring speed for complex STL formulas using value freezing.

A new approach to analyze reachability in systems influenced by randomness.

New methods using reinforcement learning improve control of complex systems.

Discover how Koopman operators improve robot learning and adaptability.

New control method improves positioning accuracy in lithographic systems for semiconductors.

This article presents methods to stabilize parabolic equations with control systems against disturbances.

A new model improves communication and reduces power use in wireless control systems.

This study seeks to reduce transition times between states in Brownian gyrators.

This paper examines machine learning techniques for feedback control in complex systems.