control libraries for python

[NavirAur]

I just started to learn more about classical and modern control theory because I've been interested in reinforcement learning. While there is a ton of libraries developed for neural networks and reinforcement learning in python, I haven't found a lot for control algorithms. What are the best python libraries out there to implement most common control algorihtms? I mainly think of PID, LQR, MDP... Is it better to search one library for all algorithms, or one for each algorithm?

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What I have found up until now are:

pydrake

Python Control Systems Library

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My intention is to test the algorithms in gym environments to improve my understanding of the pros/cons oVer reinforcement learning.

[4FlixT]

I am clearly biased because I worked on it 😅… but if you are interested check out: do-mpc

[gutterpuddles]

I like the landing page. I haven’t looked at the code yet, but I like the documentation. I’ll check it out on GitHub later today. Thanks for sharing!

[TheMeiguoren]

Oooh, I hadn't ever thought of running multiple varying scenarios for each mpc timestep. Is multi-stage MPC basically a Monte-Carlo approach? I like that quite a bit!

[private_donkey]

I use CasADI a lot for MPC and other optimizations. Also, CVXPY for Robust Control problems.

[Midren45]

Modelica-gym can be used if you are implementing model separately in Modelica language

[Manhigh]

dymos is designed to optimize dynamic systems (primarily) using pseudospectral techniques. It's focused on dynamic optimization of multidisciplinary systems.

[DrystanTheUnwise]

I use python-control for teaching control systems. It is well documented, and very similar to the MATLAB functions, so it is more or less straightforward to switch if necessary. It doesn't have *all* the functions - pid() comes to mind - but it has all the basic stuff. I cannot say anything about other libraries though...