An open-source systems and controls toolbox for Python3.


Keywords
control-engineering, control-systems, control-theory, industrial-automation, linear-systems, linear-systems-theory, model-based-control, pid-control, pid-controller, scientific-computing
License
MIT
Install
pip install harold==1.0.3

Documentation

License Documentation Status Download Counts

harold

A control systems package for Python>=3.8.

Introduction

This package is written with the ambition of providing a full-fledged control systems software that serves a control engineer/student/researcher with complete access to the source code with permissive rights (see LICENSE file). Moreover, via working with a proper high-level computer programming language many proprietary software obstacles are avoided and users can incorporate this package into their workflow in any way they see fit.

Quick Reference and Documentation

The documentation is online at ReadTheDocs. A brief tutorial about the basics can be found under the notebooks folder to see harold in action.

Roadmap

The items that are in the pipeline and what possibly lies ahead is enumerated in our roadmap.

Useful Links

  • There is already an almost-matured control toolbox which is led by Richard Murray et al. (click for the Github page) and it can perform already most of the essential tasks. Hence, if you want to have something that resembles the basics of matlab control toolbox, you should give it a try. However, it is somewhat limited to SISO tools and also relies on SLICOT library which can lead to installation hassle and/or licensing problems for nontrivial tasks.
  • You can also use the tools available in SciPy signal module for basics of LTI system manipulations. SciPy is a powerful all-purpose scientific package. This makes it extremely useful however admittedly every discipline has a limited presence hence the limited functionality. If you are looking for a quick LTI system manipulation and don't want to install yet another package, then it might be the tool for you.
  • Instead, if you are interested in robust control you probably would appreciate the Skogestad-Python project. They are replicating the code parts of the now-classic book completely in Python. Awesome!

Help Wanted!

If you are missing out a feature, or found a bug, get in contact. Such reports and PR submissions are more than welcome!

Contact

If you have questions/comments feel free to shoot one to harold.of.python@gmail.com or join the Gitter chatroom.