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README.md

Controlpy

A library for commonly used controls algorithms (e.g. creating LQR controllers). An alternative to Richard Murray's "control" package -- however, here we do not require Slycot.

Current capabilities:

  1. System analysis:
    1. Test whether a system is stable, controllable, stabilisable, observable, or stabilisable.
    2. Get the uncontrollable/unobservable modes
    3. Compute a system's controllability Gramian (finite horizon, and infinite horizon)
    4. Compute a system's H2 and Hinfinity norm
  2. Synthesis
    1. Create continuous and discrete time LQR controllers
    2. Full-information H2 optimal controller
    3. H2 optimal observer
    4. Full-information Hinf controller

How to install

Install using pypi, or direct from the Github repository:

  1. Clone this repository somewhere convenient: git clone https://github.com/markwmuller/controlpy.git
  2. Install the package (we'll do a "develop" install, so any changes are immediately available): pip install -e . (you'll probably need to be administrator)
  3. You're ready to go: try running the examples in the example folder.

Testing

If you want to run the unit tests, you'll need to install cvxpy.

Licensing

(c) Mark W. Mueller 2016

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

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