Reinforcement learning for flight control
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Updated
Aug 21, 2024 - Python
Reinforcement learning for flight control
LATEX report of my literature study into stable variable impedance learning.
This repository contains adaptive control algorithms for managing a single-phase microgrid, along with a Virtual Hardware-in-the-Loop (VHIL) simulation using Typhoon HIL Control Center.
Turn any electrical irrigation valve into a smart-valve.. or run your pumps on a smart schedule based on your climate! This homebridge plugin exposes a multi-zone irrigation sprinkler dummy control system to Apple's HomeKit. Although a dummy, it brings smarts of an evapotranspiration based climate and plant adaptive irrigation controller with th…
Like reinforcement learning, but it works in practice
Adaptive Automatic Equalizer
Welcome to my project portfolio! I am Arham Rahim, an AI and data analysis enthusiast dedicated to leveraging technology for sustainability. This repository showcases a collection of my projects, highlighting my skills and expertise in machine learning, data analytics, and sustainable innovation.
Simulation and Experiment Projects for the Paper "Desired Model Compensation-Based Position Constrained Control of Robotic Manipulators" using MATLAB Simulink and C
Fully Adaptive Network monitoring experiments for Paper.
An algorithm composed in the arc of Cybernetics. A framework that controls a machine's behaviour subjected to constantly-changing parameters, where it remembers and adapts its operational runtime
Comparison of different control algorithms for a robotic arm. Miniprojects from the course "Control Theory in Robotics" during my 1st semester of the Master's.
DiffTune is a framework to automatically tune the parameters for a controller using gradient descent.
This repository focused on enhancing the Active Inference Controller (AIC) for robotic manipulation tasks on an Interbotix PincherX 150 5-DOF Robot. A modified control framework called the Reactive Active Inference Controller (ReAIC) outperfors the AIC in adaptation experiments.
Adaptive technology in homes for linking and integrating applications.
A collection of embedded PID (Proportional – Integral – Derivative) controller tuning methods.
A Sharing Framework for Energy and Computing Resources in Multi-Operator Mobile Networks
Smart Energy Policies for Sustainable Mobile Networks via Forecasting and Adaptive Control
Parameter estimation and MRAC algorithms implemantaion
Dynamic adaptive learning for precise control of strict-feedback nonlinear systems. Harnessing TensorFlow, it seamlessly incorporates reinforcement learning techniques, such as actor-critic, ensuring efficient and resilient adaptation of the control system.
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