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A series of GUI applications, tools and programs for plotting and analysing classical and modern control systems. All applications have been built using Python, matplotlib, and python-control.

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BenjaminFraser/Control_engineering_apps

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CONTROL ENGINEERING ANALYSIS AND SIMULATION APP


INTRODUCTION

The control engineering app is designed to provide quick and convenient analysis of a wide range of control system elements within the field of both classical and modern (digital) control. All plots generated are interactive and can be analysed effectively from a given algebraic s-domain and/or z-domain transfer function.

The application is built using Python, with a tkinter GUI, and operates using python control, matplotlib, scipy and numpy.

Classical Control Systems Examples

application overview example

application plot examples

application time domain examples

Digital Control Systems Examples

application discrete time examples

application discrete time domain example

application discrete time domain example


ACCESSING THE APPLICATION/SYSTEM

The application is designed in Python 3.4, but has been tested to work on Python 2.7. To setup the system for use, you'll need to ensure you have installed all the necessary libraries, including numpy, scipy, matplotlib and python-control. The easiest, and most accessible means of operating data science related libraries such as these is to use Anaconda. Conversely, you can manually install and manage using pip install, however I'd recommend at least using a virtual environment.


Example use cases and images

Nyquist plots - for both classical and digital system analysis

application nyquist plot

Root-Locus plots - in both the s-domain and z-domain, as required.

application root locus


Author

Benjamin Fraser

Date created: 29/07/2017

Date last modified: 4/08/2017


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A series of GUI applications, tools and programs for plotting and analysing classical and modern control systems. All applications have been built using Python, matplotlib, and python-control.

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