Here, you will find various works that I have done during my time at the University of California Berkeley as part of my Capstone project.
In this section, I have developed a model predictive controller for an autonomous racing car. I have used a variety of methods, including early prototyping in Jupyter Notebooks and Pyomo, followed by more implementable approaches in a class form in Pyomo. Additionally, I have developed a low fidelity simulator that is used in the Jupyter Notebooks. This section also includes the development of estimators for inaccessible states such as wheel slip angles and slip ratios. Lastly, I have included the code used to derive the mathematical model.
I have also included the code for modifying Monster files as required for implementation in ChassisSim, a lap time simulator.
This section contains drawings for the development of a fixture that connects two motors to the same shaft in order to meet torque requirements.
I have created documentation to clarify the rationale behind the model predictive controller and to document its results. More documentation will be added in the future.
Thank you for visiting my repository and checking out my work! If you have any questions or feedback, feel free to reach out. Roar! 🚀🏎️🔥