The integration of deep reinforcement learning with PD control in humanoid robots enhances gait stability and patient comfort during lower limb rehabilitation.

More engineers are turning to reinforcement learning to incorporate adaptive and self-tuning control into industrial systems. It aims to strike a balance between traditional ...

The evolution of safety-critical autonomous systems, including agile drones and surgical robots, has fundamentally increased the demands for control design.

Scientists have observed a new microscopic mechanism enabling precise control of the magneto-optical properties of excitons in alloys of two-dimensional semiconductors. This discovery opens up ...

Abstract: This paper presents a nonlinear control strategy for grid-forming converters (GFCs) that facilitates the integration of converter-interfaced systems into the grid. For large-scale ...

Abstract: This paper presents a novel approach to practical nonlinear model predictive control (PNMPC) using Kolmogorov–Arnold networks (KANs) as prediction models. KANs are based on the ...

A multivariate analysis of electroencephalography activity reveals super-additive enhancements to the neural encoding of audiovisual stimuli, providing new insights into how the brain integrates ...

This project features a complete control pipeline for a prosthetic arm, moving from basic serial communication to complex Inverse Kinematics and a Graphical User Interface (GUI). Hardware Setup ...

This directory contains the Alpasim controller, which models vehicle dynamics and control. The controller receives trajectory reference commands, which are possibly delayed, along with state ...