# Introduction¶

Welcome to the Python Control Systems Toolbox (python-control) User’s Manual. This manual contains information on using the python-control package, including documentation for all functions in the package and examples illustrating their use.

## Overview of the Toolbox¶

The python-control package is a set of python classes and functions that implement common operations for the analysis and design of feedback control systems. The initial goal is to implement all of the functionality required to work through the examples in the textbook Feedback Systems by Astrom and Murray. A MATLAB compatibility package (control.matlab) is available that provides many of the common functions corresponding to commands available in the MATLAB Control Systems Toolbox.

## Some Differences from MATLAB¶

The python-control package makes use of NumPy and SciPy. A list of general differences between NumPy and MATLAB can be found here.

In terms of the python-control package more specifically, here are some thing to keep in mind:

- You must include commas in vectors. So [1 2 3] must be [1, 2, 3].
- Functions that return multiple arguments use tuples
- You cannot use braces for collections; use tuples instead

## Installation¶

The python-control package may be installed using pip or the standard distutils/setuptools mechanisms.

To install using pip:

```
pip install slycot # optional
pip install control
```

Alternatively, to use setuptools, first download the source and unpack it. To install in your home directory, use:

```
python setup.py install --user
```

or to install for all users (on Linux or Mac OS):

```
python setup.py build
sudo python setup.py install
```

The package requires numpy and scipy, and the plotting routines require matplotlib. In addition, some routines use a module called slycot, which is a Python wrapper around some FORTRAN routines. Many parts of python-control will work without slycot, but some functionality is limited or absent, and installation of slycot is recommended. For more information, see the GitHub repository for slycot.

## Getting Started¶

There are two different ways to use the package. For the default interface
described in *Function reference*, simply import the control package as follows:

```
>>> import control
```

If you want to have a MATLAB-like environment, use the *MATLAB compatibility module*:

```
>>> from control.matlab import *
```