AMPyC
GitHub | PyPI | Issues | Changelog
ampyc -- Advanced Model Predictive Control in Python
General Python package for control theory research, including some reference implementations of various advanced model predictive control (MPC) algorithms.
Features:
- Implements dynamical systems and control interfaces to allow seamless interactions
- Provides abstract base classes to allow custom implementation of any type of dynamical system and controller
- Reference implementations of many advanced MPC algorithms; for a full list of implemented algorithms see below
- Global parameter management for easy experiment setup and management
- Various utility tools for set computations, polytope manipulation, and plotting
- Lecture-style notes and notebook tutorials explaining advanced predictive control concepts
Installation
ampyc requires Python 3.10 or higher. Just use pip for Python 3 to install ampyc and its dependencies:
python3 -m pip install ampyc
Local (editable) installation
- Clone this repository using
git clone git@github.com:IntelligentControlSystems/ampyc.git
- Install all dependencies (preferably in a virtual environment) using
python3 -m pip install -r requirements.txt
- Install
ampycin editable mode for development. Navigate to this top-level folder and run
pip install -e .
Getting Started
To get started with the ampyc package, run the tutorial notebook, which provides an introduction to all parts of the package.
For specific control algorithms implemented in ampyc, run the associated notebook in the notebook folder.
Implemented Control Algorithms
Cite this Package & Developers
If you find this package/repository helpful, please cite our work:
@software{ampyc,
title = {AMPyC: Advanced Model Predictive Control in Python},
author = {Sieber, Jerome and Didier, Alexandre and Rickenbach, Rahel and Zeilinger, Melanie},
url = {https://github.com/IntelligentControlSystems/ampyc},
month = jun,
year = {2025}
}
Principal Developers
Metadata
Release files for ampyc 0.0.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ampyc-0.0.3.tar.gz | 67.4 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ampyc-0.0.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 67.5 MB
Release files / ampyc-0.0.3.tar.gz
| Download URL | ampyc-0.0.3.tar.gz |
|---|---|
| Size | 67.4 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
18bb8ec46b06b1afdd07a5341fbc8a013062fe6349163b328bc17304edb2958b
|
|
BLAKE2b-256 checksum How to use checksums |
93a7f0d3ff6dd20dfb665d4d8a125d1b5c5a8636e8b1192adafa67d2210f1b33
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.11.14
|
Release files / ampyc-0.0.3-py3-none-any.whl
| Download URL | ampyc-0.0.3-py3-none-any.whl |
|---|---|
| Size | 63.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
e121d5581db1c97ca703ae77f19479e346add1126c70a0cdf547bc539a6a3433
|
|
BLAKE2b-256 checksum How to use checksums |
52f807e2c2fb012def169fd327cdd0ff262e53ed1de564faec58a6b44cd338f2
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.11.14
|