A Guide for Understanding and Implementing Optimal Control for Autonomous Vehicles
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A Guide for Understanding and Implementing Optimal Control for Autonomous Vehicles

Abstract

There is a notable gap in existing autonomous vehicle control literature that providescomprehensive guides bridging control design theory to its real-world implementation. The primary objective of this thesis is to address this gap by facilitating a clear understanding of the control design process, allowing readers to seamlessly transition from theory to application in implementing controllers for autonomous vehicles. This thesis is designed to operate as a user’s manual, divided into two parts, providing a guide for the understanding of the theoretical background of autonomous vehicles, discussed in Chapter 1, followed by a detailed guide on the procedures for implementing control theory on physical autonomous vehicles, discussed in Chapter 2. Topics such as vehicle modeling, state estimation, system identification, and control are covered in Chapter 1, while Chapter 2 guides the reader through the core algorithms used, the utilization of the autonomous vehicle framework and detailed experimental procedures for data collection and controller testing, both in simulation and on the physical vehicle. Tailored for a broad educational audience, this thesis assumes only a foundational knowledge of Linux systems, linear algebra, differential equations, and basic physics related to moving objects.

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