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): python setup.py develop (you'll probably need to be administrator)
3. You're ready to go: try running the examples in the example folder.

Licensing

(c) Mark W. Mueller 2015

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/.