AI 中文总结
该研究针对自主路径跟踪问题，提出基于误差空间的线性化数据驱动预测控制算法，结合纵向车速调度，经高保真仿真测试验证了其用于车辆控制的潜力。
AI 中文摘要
近年来，基于信息系统轨迹而非物理模型的预测控制受到广泛关注。本文研究将此类数据驱动控制用于车辆动力学控制与自主路径跟踪的潜力，通过将路径跟踪问题置于误差空间考虑， underlying系统近似线性，可应用现有数据驱动预测控制成果，还可方便地引入基于纵向车速的调度。所提控制算法在高保真仿真环境中针对两种不同变道机动进行了测试。
英文摘要
Predictive control based on an informative system trajectory, instead of a physics-based model, has received significant attention in recent years. This paper investigates the potential of using such data-driven control for vehicle dynamics control and autonomous path following. By considering the path following problem in the error space, the underlying system is approximately linear and existing results for data-driven predictive control can be applied. Also, scheduling based on longitudinal speed can be readily included. The proposed control algorithm was tested on two different lane change maneuvers in a high-fidelity simulation environment.
Comments6 pages, 6 figures
Journal refProc. 2023 27th Int. Conf. Syst. Theory Control Comput. (ICSTCC), 2023, pp. 368-373
DOI：10.1109/ICSTCC59206.2023.10308482
