Enhao Wang enhao.wang@durham.ac.uk
PGR Student Doctor of Philosophy
Path tracking control is a core technology of intelligent vehicles, and the accuracy of tracking performance is a key element of this technology. In order to address the issue of low accuracy in traditional methods for solving intelligent vehicle path tracking problems, a fast and high-precision solution method was design. This method discretized the continuous optimal control problem at collocation points and approximated the state and control variables through global interpolation polynomials, thereby transforming the optimal control problem of intelligent vehicle path tracking into a nonlinear programming NLP problem for solution. Finally, the real vehicle test verified the effectiveness of the method. The simulation results and comparison with traditional methods show that this method can solve the intelligent vehicle path tracking problem with high accuracy and has good engineering application potential.
Wang, E., Liu, Y., & Xie, C. (2025). Optimal Control of Intelligent Vehicle Path Tracking. IEEE Access, 13, 60148-60157. https://doi.org/10.1109/ACCESS.2025.3557215
Journal Article Type | Article |
---|---|
Acceptance Date | Mar 31, 2025 |
Online Publication Date | Apr 2, 2025 |
Publication Date | Apr 2, 2025 |
Deposit Date | May 29, 2025 |
Publicly Available Date | May 29, 2025 |
Journal | IEEE Access |
Electronic ISSN | 2169-3536 |
Publisher | Institute of Electrical and Electronics Engineers |
Peer Reviewed | Peer Reviewed |
Volume | 13 |
Pages | 60148-60157 |
DOI | https://doi.org/10.1109/ACCESS.2025.3557215 |
Public URL | https://durham-repository.worktribe.com/output/3967141 |
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