Comparing-Machine-Learning-based-Methods-MPC-BOPTEST

This repository implements the scientific paper "Comparing Machine Learning based Methods MPC BOPTEST". The purpose of this project is to provide a concrete and comprehensive comparison of machine learning methods in the context of Model Predictive Control (MPC) using the BOPTEST HVAC simulator.

Disclaimer

Please note that while this repository implements the methodology outlined in the paper "Comparing Machine Learning based Methods MPC BOPTEST", I am not one of the original authors of that paper. This implementation is meant to be a resource for further research and development in this field, and all credit for the original methodology and ideas goes to the original authors of the paper.

Repository Structure

This repository is organized as follows:

├── 0_generate_dataset.py # Script for generating the dataset
├── 1_train_model.py # Script for training the model
├── 2_eval_model.py # Script for evaluating the model
├── 3_make_experiment.py # Script for running experiments
├── boptest.py # Main BOPTEST interface
├── _cache_models # Cached models for quick reloading
├── controller # Control logic and algorithms
├── dataset # Data for training and testing
├── env.py # Environment setup and variables
├── LICENSE # License details
├── models # Models and Model architecture ressources
├── project1_boptest # Project-specific BOPTEST configurations
├── pycache # Cached Python bytecode
├── README.md 
└── TODO # Planned features and improvements

Installation

Clone this repository to your local machine using https://github.com/Enderdead/Comparing-Machine-Learning-based-Methods-MPC-BOPTEST.git.
Ensure that you have the necessary Python packages installed. (You can list these in a requirements.txt file for easy installation with pip install -r requirements.txt.)

Usage

To use this project, follow these steps:

Generate the dataset by running python 0_generate_dataset.py.
Train the model by running python 1_train_model.py.
Evaluate the model by running python 2_eval_model.py.
To make an experiment, run python 3_make_experiment.py.

Contributing

We welcome contributions to this project. Please feel free to submit a pull request or open an issue for discussion.

License

This project is licensed under the terms of the GNU-V3 License. For more details, see the LICENSE file.

Acknowledgements

We would like to thank the authors of the original "Comparing Machine Learning based Methods MPC BOPTEST" paper for their contributions to the field.

Enderdead/Comparing-Machine-Learning-based-Methods-MPC-BOPTEST