The accurate characterization of tire dynamics is critical for advancing control strategies in autonomous road vehicles, as tire behavior significantly influences handling and stability through the generation of forces and moments at the tire-road interface. Smart tire technologies have emerged as a promising tool for sensing key variables such as road friction, tire pressure, and wear states, and for estimating kinematic and dynamic states like vehicle speed and tire forces. However, most existing estimation and control algorithms rely on empirical correlations or machine learning approaches, which require extensive calibration and can be sensitive to variations in operating conditions. In contrast, model-based techniques, which leverage infinite-dimensional representations of tire dynamics using partial differential equations (PDEs), offer a more robust approach. This paper proposes a novel model-based, output-feedback lateral tracking control strategy for all-wheel steering vehicles that integrates distributed tire dynamics with smart tire technologies. The primary contributions include the suppression of micro-shimmy phenomena at low speeds and path-following via force control, achieved through the estimation of tire slip angles, vehicle kinematics, and lateral tire forces. The proposed controller and observer are based on formulations using ODE-PDE systems, representing rigid body dynamics and distributed tire behavior. This work marks the first rigorous control strategy for vehicular systems equipped with distributed tire representations in conjunction with smart tire technologies.

翻译：轮胎动力学的精确表征对于推进自动驾驶道路车辆的控制策略至关重要，因为轮胎行为通过轮胎-路面界面产生的力和力矩显著影响车辆的操纵性与稳定性。智能轮胎技术已成为一种有前景的工具，可用于感知关键变量（如路面摩擦、胎压和磨损状态）以及估计运动学和动力学状态（如车速和轮胎力）。然而，现有的大多数估计与控制算法依赖于经验相关性或机器学习方法，这些方法需要大量校准，且对工况变化较为敏感。相比之下，基于模型的技术利用偏微分方程（PDEs）对轮胎动力学进行无限维表示，提供了一种更稳健的方法。本文提出了一种新颖的基于模型、输出反馈的全轮转向车辆横向跟踪控制策略，该策略将分布式轮胎动力学与智能轮胎技术相结合。主要贡献包括通过估计轮胎侧偏角、车辆运动学及轮胎侧向力，实现了低速微幅摆振现象的抑制以及基于力控制的路径跟踪。所提出的控制器与观测器基于ODE-PDE系统公式构建，分别表征刚体动力学与分布式轮胎行为。此项工作首次为配备分布式轮胎表征并结合智能轮胎技术的车辆系统提出了严格的控制策略。