This is a course on principles of automatic control using classical control theory. The course uses Python to implement some of the concepts described in class.
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The notebooks run with python 3.9 and use the following python libraries:
- sympy
- python control
- numpy
- pandas
- matplotlib
- opencv-python
Notebook 01_Getting_started_with_Python_and_Jupyter_Notebook.ipynb provides a short introduction on how to set up an anaconda environment to get you started.
Each notebook is thought to be independent from every other, so it is possible to run them in any order you prefer.
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Images above are from the paper Conlan Cesar, Benjamin Whetton, Michael DeFilippo, Michael Benjamin, Michael Sacarny, Scott Reed, Andrea Munafo, Coordinating Multiple Autonomies to Improve Mission Performance, OCEANS 2021 MTS/IEEE, October, 2021
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Some of the images and content used in the notebooks have been based on resources available from engineeringmedia.com. The website and the youtube videos are a fantastic resource on control systems.
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The pendulum example is inspired by Control tutorials for Matlab and Simulink
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Relevant textbooks used to prepare these notebooks are reported in
00_Syllabus.ipynb.
- Control systems academy
- Process Dynamics and Control in Python
- Karl J. Åström and Richard M. Murray, Feedback Systems: An Introduction for Scientists and Engineers
- Lecture series on Control Engineering by Prof. Madan Gopal
- Designing Lead and Lag Compensators in Matlab and Simulink