J Shanghai Jiaotong Univ Sci ›› 2023, Vol. 28 ›› Issue (1): 114-125.doi: 10.1007/s12204-023-2574-2
收稿日期:
2022-03-21
出版日期:
2023-01-28
发布日期:
2023-02-10
HUANG Yinggang1 (黄迎港), LUO Wenguang1∗ (罗文广), HUANG Dan2 (黄 丹), LAN Hongli1 (蓝红莉)
Received:
2022-03-21
Online:
2023-01-28
Published:
2023-02-10
摘要: 在超高速以及恶劣行驶条件下,传统控制方法难以同时保证无人车在转弯过程中的路径跟踪精度和驾驶稳定性。因此,本研究提出一种无人车辆路径跟踪串级控制策略。考虑基于车辆轮胎侧滑和道路曲率影响建立一种新的车辆误差模型,采用前馈-参数自适应线性二次调节器(LQR)和比例积分(PI)控制算法设计速度保持控制器来组成无人车路径跟踪串级控制器。为提高无人车在恶劣驾驶条件下的适应性,使用BP神经网络自动调整LQR控制器参数,其中初始权值和阈值根据驾驶条件使用改进的灰狼优化算法进行优化;保速控制器提高了在非线性车速变化下的曲线跟踪精度。最后,建立MATLAB/Simulink和CarSim的联合模型,仿真结果表明:所提出的控制方法可以实现无人车在超高速下的保速过弯能力。在强风和冰雪路面条件下,该方法表现出更高的跟踪精度,与前馈-LQR、单点预瞄控制和纯追踪控制等方法相比,在驾驶和变曲率路面上对外界干扰的适应性和鲁棒性更强。
中图分类号:
. 恶劣行驶条件下无人车辆路径跟踪串级优化控制[J]. J Shanghai Jiaotong Univ Sci, 2023, 28(1): 114-125.
HUANG Yinggang1 (黄迎港), LUO Wenguang1∗ (罗文广), HUANG Dan2 (黄 丹), LAN Hongli1 (蓝红莉). Cascade Optimization Control of Unmanned Vehicle Path Tracking under Harsh Driving Conditions[J]. J Shanghai Jiaotong Univ Sci, 2023, 28(1): 114-125.
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