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<p>Trajectory tracking and yaw stability are conflicting objectives for autonomous vehicles, as improving tracking precision often compromises lateral stability. This paper proposes a coordinated control strategy integrating model predictive control (MPC) for trajectory tracking with H infinity control for yaw stability maintenance. A hierarchical framework is established where the upper layer employs MPC with adaptive preview distance to generate optimal front steering angles, while a stability controller computes additional yaw moments via gain-scheduled H infinity theory. An adaptive coordination mechanism based on a normalized stability index dynamically adjusts the reference yaw rate and stability intervention intensity, effectively resolving control conflicts. The lower layer implements a multi-objective torque allocation optimization that minimizes tracking error, tire utilization ratio, and slip power loss through quadratic programming. Simulation results under DLC scenario demonstrate that the proposed strategy maintains lateral deviation within 0.05&#xa0;m under high adhesion conditions, while significantly improving yaw stability under low adhesion. Comparative analysis shows the integrated MPC-H infinity approach outperforms PID-NTSMC and PID-H infinity combinations in both tracking precision and stability, with smoother front wheel steering angle and reduced sideslip fluctuations.</p>

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Coordinated Trajectory Tracking and Yaw Stability Control for Autonomous Vehicles via Integrated MPC and H Infinity Control

  • 期刊论文

  • 发表日期：

    2026年7月1日

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  • Yaoyang Chen,
  • Youqun Zhao,
  • Danyang Li,
  • Fen Lin,
  • Liguo Zang

摘要

Trajectory tracking and yaw stability are conflicting objectives for autonomous vehicles, as improving tracking precision often compromises lateral stability. This paper proposes a coordinated control strategy integrating model predictive control (MPC) for trajectory tracking with H infinity control for yaw stability maintenance. A hierarchical framework is established where the upper layer employs MPC with adaptive preview distance to generate optimal front steering angles, while a stability controller computes additional yaw moments via gain-scheduled H infinity theory. An adaptive coordination mechanism based on a normalized stability index dynamically adjusts the reference yaw rate and stability intervention intensity, effectively resolving control conflicts. The lower layer implements a multi-objective torque allocation optimization that minimizes tracking error, tire utilization ratio, and slip power loss through quadratic programming. Simulation results under DLC scenario demonstrate that the proposed strategy maintains lateral deviation within 0.05 m under high adhesion conditions, while significantly improving yaw stability under low adhesion. Comparative analysis shows the integrated MPC-H infinity approach outperforms PID-NTSMC and PID-H infinity combinations in both tracking precision and stability, with smoother front wheel steering angle and reduced sideslip fluctuations.