do-dpc 1.0.0

Framework software package for the Data-Driven Predictive Control (DPC) algorithm with visual examples.

Do DPC

The purpose of this code is to provide a Framework for Data-Driven Predictive Control (DPC) with illustrative examples.

Please visit the extensive documentation, kindly hosted on readthedocs.

Citing do-dpc

Please follow the instructions if you want to use do-dpc for published work.

Getting Started

This library utilizes the Mosek Solver. While it is possible to use any solver compatible with CVXPY, it is recommended to use Mosek for optimal performance. Please follow the installation instructions on the Mosek website to set it up.

To ensure a clean and isolated development environment, it is recommended to use Python's virtual environment (venv).

Linux / macOS

python3.12 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Windows

py -m venv venv
.\venv\Scripts\activate
pip install -r requirements.txt

Building the documentation

Navigate to the docs Folder:

cd docs

Create and activate a virtual environment:

python3.12 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Generate the documentation:

make html

Once the HTML files are created, you can serve them locally:

python -m http.server --directory build/html 8000

Open your browser and visit:

http://localhost:8000

Folder structure

The code contains the following files and folders:

do-dpc/
├── do_dpc/                      # Core Python source code for the DPC library
│   ├── control_utils/            # Utilities for control systems (PID, noise generators, etc.)
│   ├── dpc/                     # Core DPC algorithms and implementations
│   │   ├── dpc.py               # Main DPC implementation
│   │   ├── dpc_structs.py       # Data structures for DPC
│   ├── utils/                    # General utility modules (logging, path management, etc.)
├── docs/                         # Documentation files (Sphinx)
│   ├── build/                    # Build artifacts for generated documentation
│   ├── source/                   # Source files for documentation
│   │   ├── _static/              # Static assets (images, CSS, etc.)
│   │   ├── _templates/           # Templates for documentation structure
│   │   ├── dpc_methods/         # Documentation for different DPC methods
│   │   ├── getting_started/      # Guides and introductory documentation
│   │   ├── conf.py               # Sphinx configuration file
│   │   ├── index.rst             # Main entry point for documentation
│   ├── .readthedocs.yaml         # Configuration for Read the Docs
│   ├── Makefile                  # Makefile for building the documentation
│   ├── make.bat                  # Windows batch script for building documentation
├── tests/                        # Test suite for the DPC library
│   ├── fixtures/                 # Pytest fixtures for setting up test cases
│   ├── system_tests/             # System-level integration tests
│   ├── unit_tests/               # Unit tests for individual modules
├── .gitlab-ci.yml                # CI/CD pipeline configuration for GitLab
├── .pylintrc                     # Linter configuration for Python code
├── CITATION.cff                  # Citation file for academic references
├── confest.py                    # Pytest configuration file
├── LICENSE.txt                   # Licensing information
├── README.md
├── requirements.txt
└── setup.py                      # Setup script for packaging and installation