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tinympc-python's Introduction

TinyMPC: Model-Predictive Control on Resource-Constrained Microcontrollers

If you have any questions related to the solver, visit the GitHub Discussions page. This guarantees accessibility for everyone.

The documentation is available at tinympc.org

High-level language interfaces with detailed examples and code generation are available in Python, Julia, and MATLAB.

Building

  1. On terminal, clone this repo
git clone https://github.com/TinyMPC/TinyMPC.git
  1. Navigate to root directory and run
cd TinyMPC && mkdir build && cd build
  1. Run CMake configure step
cmake ..
  1. Build TinyMPC
cmake --build .

Examples

  • Run the quadrotor_hovering example
./examples/quadrotor_hovering
  • Run the codegen_cartpole example then follow the same building steps inside that directory
./examples/codegen_cartpole

Citing TinyMPC

If you are using TinyMPC, we encourage you to

  • Cite the related papers:
@inproceedings{tinympc,
      title={TinyMPC: Model-Predictive Control on Resource-Constrained Microcontrollers}, 
      author={Khai Nguyen and Sam Schoedel and Anoushka Alavilli and Brian Plancher and Zachary Manchester},
      booktitle={IEEE International Conference on Robotics and Automation (ICRA)},
      year = {2024}
}
@misc{tinympc2,
      title={Code Generation for Conic Model-Predictive Control on Microcontrollers with TinyMPC}, 
      author={Sam Schoedel and Khai Nguyen and Elakhya Nedumaran and Brian Plancher and Zachary Manchester},
      year={2024},
      eprint={2403.18149},
      archivePrefix={arXiv},
}

  • Put a star ⭐ on this repository.

Excited to hear your TinyMPC success stories—share them with us!

Bug reports and support

Please report any issues via the Github issue tracker. All types of issues are welcome including bug reports, documentation typos, feature requests and so on.

Running on MCUs

Numerical benchmarks against other solvers on MCUs are available here.

Notes

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