@inproceedings{3a67056e0a9c408689e46f21292337d9,
title = "Research on FSAC trajectory tracking control based on optimized BP neural network algorithm",
abstract = "A longitudinal linear quadratic regulation LQR acceleration motion controller and a lateral linear model prediction (LTV-MPC) motion controller are designed to address the accuracy and stability of trajectory tracking with a four-wheel independent drive driverless formula car. Based on the BP neural network algorithm, the prediction step and control step parameters of the model prediction control are adaptively adjusted, and the genetic optimisation algorithm is used to optimise the BP neural network to improve the lateral trajectory tracking accuracy of the car. The simulation results show that the proposed lateral motion control strategy can control the unmanned racing car to track the lateral trajectory well during the trajectory tracking process.",
keywords = "adaptive, formula car, four-wheel independent drive, model predictive control, trajectory tracking",
author = "Zhiqiang Zhang and Gang Li and Zhixin Chen and Xing Zhang",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 7th CAA International Conference on Vehicular Control and Intelligence, CVCI 2023 ; Conference date: 27-10-2023 Through 29-10-2023",
year = "2023",
doi = "10.1109/CVCI59596.2023.10397333",
language = "English",
series = "Proceedings of the 2023 7th CAA International Conference on Vehicular Control and Intelligence, CVCI 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings of the 2023 7th CAA International Conference on Vehicular Control and Intelligence, CVCI 2023",
address = "United States",
}