This project implements a Reinforcement Learning based control system for a DC motor using the MATLAB Reinforcement Learning Toolbox and Simulink. A Deep Deterministic Policy Gradient (DDPG) ...
Pioneering studies suggested that motor information in the cortex is coded through the combined actions of large populations of widely tuned neurons rather than by small numbers of highly tuned ...
This document provides a detailed explanation of the MATLAB code that demonstrates the application of the Koopman operator theory for controlling a nonlinear system using Model Predictive Control (MPC ...
Abstract: Distributed control strategies have been widely adopted in DC microgrid (MG) secondary control owing to their flexibility. However, they often entail high communication overhead and are ...
Abstract: This Study explores ways to improve the speed of DC motors through comparison of traditional tuning methods, viz. Ziegler-Nichols and Cohen-Coon with a machine learning approach using Random ...
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