A data-driven environmental planning framework strengthens climate governance through quality control standards, interdisciplinary expertise, and predictive emission modeling. By integrating ...

In a study published in Robot Learning journal, researchers propose a new learning-based path planning framework that allows mobile robots to navigate ...

Abstract: Grid-forming voltage source converters (VSCs) are regarded as a promising solution for future converter-dominated power systems, but they still demand advanced control schemes to realize ...

This project focuses on system identification and PID controller design using measured response data. The objective was to model the system dynamics and improve performance through closed-loop control ...

This repository contains MATLAB codes for solving Linear Quadratic Regulator (LQR) problems using model-free Reinforcement Learning (RL) techniques. It includes methods such as Policy Iteration, Value ...

Abstract: The first course of control is under a critical review. Both the teaching material covered and the teaching methods require new considerations. Introducing interactivity in the education ...

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

During the acquisition of correct rejection response, rankings of functional connection separated for cortical and subcortical regions, which is predictive of the peak timing of visual information ...

Allen Control Systems (ACS), a leader in autonomous precision robotics, today announced the tripling of its Austin, Texas operations to more than 57,000 square feet to meet the de ...

The 25th Infantry Division is testing a new command-and-control system designed to speed how the Army detects threats, makes ...