Dear Students,
Here you can download the simulation codes used in this course.

LICENSE AGREEMENT
In relation to the Python files uploaded in this lecture:
1. Copyright of the Python files uploaded in this lecture  are owned by the author: Mark Misin
2. The Python codes uploaded in this lecture can be freely used and distributed
3. The copyright label in the Python files uploaded in this lecture such as
copyright=ax_main.text(x,y,'© Mark Misin Engineering',size=z)
that indicate that the Copyright is owned by Mark Misin MUST NOT be removed.

WARRANTY DISCLAIMER!
The python files uploaded in this lecture are an extra part for the course in hope to give extra value to it. It comes with absolutely NO WARRANTY! In no event can the author of the Python files uploaded in this lecture be held responsible for whatever happens in relation to these python files. For example, if there is a bug in the codes and because of that a project, invention, or something else it is used for fails - the author is NOT RESPONSIBLE!

IMPORTANT 1 - You have to run the file: MAIN_LPV_MPC_car_lateral.py
This file has to be in the same folder with the file: support_files_car.py

IMPORTANT 2 - You need Python 3, Numpy, and Matplotlib to run them. Please refer to the 3 first videos at the beginning of this section for installation instructions.

Also, it is better to run the code either from Windows command prompt or Linux terminal. If you use IDEs such as Spyder or Jupyter notebook, it might not run the simulation.

IMPORTANT 3 - Please leave me a review! I would love to hear from you! :)

THE KEY REFERENCES FOR MPC TRACKING:

Model Predictive control:
Optimal and Robust control course at CTU in Prague (L3.4 - Introduction to Model Predictive Control (MPC) - reference tracking)
(The course is closed; however, their videos can be watched on YouTube for free and without the need to register anywhere: Click here)
Please note that in L3.4, small errors in the MPC Mathematical derivation were discovered, which were corrected in this course.

Best Regards,
Mark Misin