Scholarlink

<p>To improve the path tracking accuracy of the four-wheel-steering vehicle while maintaining driving stability, a path-tracking method that fuses model predictive control and extension control is proposed in this paper. First, the front and rear tire forces are linearized and segmented, and a vehicle–road model with four-wheel steering is established. Then, considering the characteristics of path tracking and stability control of the four-wheel-steering vehicle across different vehicle–road states, the extension controller is designed to determine the relationship coefficients between the front and rear wheel steering angles of the four-wheel-steering vehicle based on the theory of extension control. Building upon the established vehicle–road model, a model predictive controller is developed through rigorous optimization to generate coordinated steering commands for the front and rear wheels. This control architecture strategically incorporates lateral slip angles of the front and rear wheels as real-time constraints, while also accounting for path tracking precision and vehicle stability. The co-simulation results of CarSim and Simulink show that the proposed method effectively handles different vehicle–road environments and improves path-tracking accuracy while maintaining vehicle stability.</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

Path Tracking Based on Extension Control and MPC for Intelligent Vehicle with Four-Wheel Steering

  • 期刊论文

  • 发表日期：

    2026年3月26日

查看全文
  • Huiran Wang,
  • Yuan Liu,
  • Wuwei Chen,
  • Qidong Wang,
  • Linfeng Zhao,
  • Siyu Peng,
  • Maofei Zhu

摘要

To improve the path tracking accuracy of the four-wheel-steering vehicle while maintaining driving stability, a path-tracking method that fuses model predictive control and extension control is proposed in this paper. First, the front and rear tire forces are linearized and segmented, and a vehicle–road model with four-wheel steering is established. Then, considering the characteristics of path tracking and stability control of the four-wheel-steering vehicle across different vehicle–road states, the extension controller is designed to determine the relationship coefficients between the front and rear wheel steering angles of the four-wheel-steering vehicle based on the theory of extension control. Building upon the established vehicle–road model, a model predictive controller is developed through rigorous optimization to generate coordinated steering commands for the front and rear wheels. This control architecture strategically incorporates lateral slip angles of the front and rear wheels as real-time constraints, while also accounting for path tracking precision and vehicle stability. The co-simulation results of CarSim and Simulink show that the proposed method effectively handles different vehicle–road environments and improves path-tracking accuracy while maintaining vehicle stability.