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

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.

(c) Mark W. Mueller 2014