Paper
27 October 2023 Improved model predictive control for autonomous racecar trajectory tracking
Yingjie Fu, Guogang Liu, Yihang Cheng
Author Affiliations +
Proceedings Volume 12922, Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023); 129220S (2023) https://doi.org/10.1117/12.3009023
Event: The Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023), 2023, Xiamen, China
Abstract
The China University Student Formula Autonomous Driving Competition is the most prestigious innovation competition in the series of events initiated by the Society of Automotive Engineers of China (SAE-China) Science Popularization Center. In comparison to traditional racing, the focus of the autonomous formula competition lies in the autonomous driving capabilities of the race cars. Wire-controlled steering is a critical component of the lateral control system. This paper presents a nonlinear model predictive controller designed using a dynamic hybrid particle swarm optimization algorithm. Building upon the simplified two-degree-of-freedom vehicle model, the traditional model predictive control algorithm is improved by utilizing the dynamic hybrid particle swarm optimization algorithm to solve the optimization function. Finally, a joint simulation using Simulink and CarSim is conducted to validate the enhanced model predictive controller, demonstrating its superior tracking accuracy and driving stability. The objective of this paper is to provide design guidelines for the WUTA team in the 2023 season and share the experience in designing a steering controller with other autonomous formula racing teams.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yingjie Fu, Guogang Liu, and Yihang Cheng "Improved model predictive control for autonomous racecar trajectory tracking", Proc. SPIE 12922, Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023), 129220S (27 October 2023); https://doi.org/10.1117/12.3009023
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KEYWORDS
Particle swarm optimization

Nonlinear control

Autonomous vehicles

Detection and tracking algorithms

Device simulation

Motion models

Control systems

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