Latest Articles for Control Systems

This article studies how the iP controller manages stability in linear control systems.

A new PD controller enhances the performance of flexible joint robots.

A novel method for reducing model complexity while maintaining essential features.

A new method for safely controlling unpredictable systems.

This article explores stochastic differential equations and their applications in managing uncertainty.

A new method enhances safety for robots navigating complex environments.

This article discusses control strategies in leader-follower games with private information.

New methods enhance safety for complex systems like robots and autonomous vehicles.

Research focuses on improving control strategies for nonlinear systems using data.

New methods improve control design for complex robotic specifications.

This article explores the integration of reinforcement learning with stochastic optimal control for safer decision-making.

Learn strategies for controlling systems despite unknown variables.

A look at managing safety in uncertain environments for autonomous systems.

Examining formation control techniques for multiple agents using distance and bearing constraints.

Researchers develop a method for efficient robot control across different designs.

A new method allows autonomous vehicles to be controlled without real-world data.

New methods use graph theory to enhance structural controllability in switched systems.

A new approach enhances self-driving race car performance using real-time learning.

A new framework for improving safety and performance in hybrid robotic systems.

New Model Predictive Control approach enhances safety in robotic systems.

This article discusses how DPETS improves stability and control in reinforcement learning.

A look at control systems and the role of state estimation in technology management.

Learn how SMPC balances safety and performance in uncertain systems.

An overview of Distributionally Robust Model Predictive Control in uncertain environments.

A new method improves control for engine-driven ducted fan lift systems.

A method using deep reinforcement learning and reactive synthesis for controller design.

A new method enhances model training for better future predictions.

This article presents a method for optimizing PID controllers in balancing robots.

Exploring model-free control techniques under limited communication channels.

This paper presents a fresh approach to controlling large groups of systems.

New control methods improve stability for underactuated balance robots using Gaussian processes.

A look into challenges of making predictions in complex dynamical systems.

This research explores gain scheduling and neural operators for better control of nonlinear PDEs.

A study on controlling systems with Dirichlet boundary conditions for improved performance.

This article discusses strategies to control harmonic oscillators while minimizing energy use.

A new method enhances control of complex systems using data-driven techniques.

Exploring new methods to enhance Model Predictive Control with deep learning techniques.

A study on efficient reachability methods for autonomous systems.

A new method enhances robots' abilities to move efficiently on uneven surfaces.

Introducing a framework for safety filters that balances performance and safety in control systems.