# Data-driven-deep-reinforcement-learning-controller-for-DC-DC-buck-converter-feeding-CPLs

**Repository Path**: liu_sh/Data-driven-deep-reinforcement-learning-controller-for-DC-DC-buck-converter-feeding-CPLs

## Basic Information

- **Project Name**: Data-driven-deep-reinforcement-learning-controller-for-DC-DC-buck-converter-feeding-CPLs
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-12-07
- **Last Updated**: 2025-12-07

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Overview
This repository is dedicated to the dissemination of the source code for a pioneering research project on the application of data-driven deep reinforcement learning (DRL) for the control of DC-DC buck converters feeding Constant Power Loads (CPLs). <br>
This work aims to demonstrate the feasibility and efficiency of applying advanced reinforcement learning techniques directly to power electronics systems. 
Our focus is on developing a controller that can adaptively manage the dynamic environment of DC-DC converters to ensure voltage stability under various operating conditions.
# Research Contributions
The methodology and experimental results presented in this repository are based on comprehensive studies detailed in the following papers:<br>

**Paper 1:** [Voltage Regulation of DC-DC Buck Converters Feeding CPLs via Deep Reinforcement Learning](https://ieeexplore.ieee.org/abstract/document/9521987)<br>
**Paper 2:** [Implementation of Transferring Reinforcement Learning for DC–DC Buck Converter Control via Duty Ratio Mapping](https://ieeexplore.ieee.org/abstract/document/9841427)<br>
**Paper 3:** [Robustness enhancement of DRL controller for DC–DC buck convertersfusing ESO](https://www.tandfonline.com/doi/full/10.1080/23307706.2023.2201587)<br>
These papers provide the theoretical foundation and empirical evidence supporting the effectiveness of deep reinforcement learning in controlling DC-DC converters with constant power loads.<br>

# Prerequisites
Matlab 2023b

## Acknowledgements

- **Intelligent and Autonomous Systems Laboratory** (IAS Lab) at Shanghai University of Electric Power.