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:
- System analysis:
- Test whether a system is stable, controllable, stabilisable, observable, or stabilisable.
- Get the uncontrollable/unobservable modes
- Compute a system's controllability Gramian (finite horizon, and infinite horizon)
- Compute a system's H2 and Hinfinity norm
- Synthesis
- Create continuous and discrete time LQR controllers
- Full-information H2 optimal controller
- H2 optimal observer
- Full-information Hinf controller
Install using pypi, or direct from the Github repository:
- Clone this repository somewhere convenient: git clone https://github.com/markwmuller/controlpy.git
- 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)
- You're ready to go: try running the examples in the example folder.
(c) Mark W. Mueller 2014