Scholarlink

<p>The existing research on the path following of the autonomous electric vehicle (AEV) mainly focuses on the path planning and the kinematic control. However, the dynamic control with the state observation and the communication delay is usually ignored, so the path following performance of the AEV cannot be ensured. This article studies the observer-based path following control strategy for the AEV with the communication delay via a robust explicit model predictive control approach. Firstly, a projected interval unscented Kalman filter is proposed to observe the vehicle sideslip angle and yaw rate. The observer considers the state constraints during the observation process, and the robustness of the observer is also considered. Secondly, an explicit model predictive control is designed to reduce the computational complexity. Thirdly, considering the efficiency of the information transmission, the influence of the communication delay is considered when designing the observer-based path following control strategy. Finally, the numerical simulation and the hardware-in-the-loop test are conducted to examine the effectiveness and practicability of the proposed strategy.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Observer-Based Robust Explicit Model Predictive Control for Path Following of Autonomous Electric Vehicles with Communication Delay

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月1日

查看全文
  • Jing Zhao,
  • Renbin Li,
  • Mingze Lv,
  • Wenfeng Li,
  • Zhengchao Xie,
  • Pak Kin Wong

摘要

The existing research on the path following of the autonomous electric vehicle (AEV) mainly focuses on the path planning and the kinematic control. However, the dynamic control with the state observation and the communication delay is usually ignored, so the path following performance of the AEV cannot be ensured. This article studies the observer-based path following control strategy for the AEV with the communication delay via a robust explicit model predictive control approach. Firstly, a projected interval unscented Kalman filter is proposed to observe the vehicle sideslip angle and yaw rate. The observer considers the state constraints during the observation process, and the robustness of the observer is also considered. Secondly, an explicit model predictive control is designed to reduce the computational complexity. Thirdly, considering the efficiency of the information transmission, the influence of the communication delay is considered when designing the observer-based path following control strategy. Finally, the numerical simulation and the hardware-in-the-loop test are conducted to examine the effectiveness and practicability of the proposed strategy.