A real-time optimal control approach to autonomous drifting

Master thesis (2022)

Authors

A. Cador Mechanical Engineering

Contributors

T. Keviczky Team Tamas Keviczky - Mechanical, Maritime and Materials Engineering (mentor)
B. Shyrokau Intelligent Vehicles - Mechanical, Maritime and Materials Engineering (graduation committee member)
A. Bertipaglia Intelligent Vehicles - Mechanical, Maritime and Materials Engineering (graduation committee member)
Faculty
Mechanical Engineering, Mechanical Engineering
Copyright: © 2022 Andrei Cador
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Published Date

14-12-2022

Language

English

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Faculty

Mechanical Engineering

Abstract

Full vehicle automation requires complete control over all driving scenarios that can be encountered on roads in order to ensure passenger safety at all times. This extends to dangerous situations such as losing control on slippery surfaces, commonly known as drifting. This work aims to make a step toward ensuring passenger safety in these situations by gaining control over vehicle behavior in high side slip regions. As these regions tend to be highly nonlinear and drifting dynamics happen at a millisecond scale, the time availability for generating proper commands is highly restricted. This work further proposes a method based on Nonlinear Model Predictive Controller (NMPC) that conveniently splits and reformulates the drifting problem to reduce the computational burden of the control structure and make it suitable for real-time implementations. The overall performance and robustness will be evaluated in obstacle-avoidance scenarios and in more general driving situations.

Files

Thesis_Cador.pdf
(pdf | 17.8 Mb)