This paper investigates the problem of centralized look ahead (CLA) consensus of connected automated vehicles convoys (CAVC) based on sample data control in the presence of measurement delay and engine’s lag. A double-integrator model is considered to describe the 1-D motion of automated vehicles (AVs). In the practical implementation, data loss and time delay are unavoidable in CAVC networks. Therefore, these issues are considered in modeling and control design of CAVCs and a CLA consensus is defined for all following AVs. By employing the Lyapunov-Krassovskii theorem, the sufficient conditions guaranteeing the zero tracking error of CAVCs in the presence of delay and data loss are derived. Then, by doing the error proliferation analysis in the frequency domain, sufficient conditions on control parameters assuring string stability are attained. Numerical studies are carried out to confirm the performance of the proposed consensus algorithm.

本文研究了在存在测量延迟和发动机滞后的情况下，基于样本数据控制的联网自动驾驶车辆车队 (CAVC) 的集中式前瞻 (CLA) 共识问题。双积分器模型被认为是描述自动驾驶汽车 (AV) 的一维运动。在实际实现中，CAVC网络不可避免地会出现数据丢失和时延问题。因此，在 CAVC 的建模和控制设计中考虑了这些问题，并为以下所有 AV 定义了 CLA 共识。利用Lyapunov-Krassovskii定理，推导出了保证CAVC在延迟和数据丢失情况下跟踪误差为零的充分条件。然后，通过在频域中进行误差扩散分析，获得了保证串稳定性的控制参数的充分条件。