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<p>This paper introduces a hierarchical three-layer adaptive control structure aimed at improving vehicle lateral stability under parametric uncertainties and unknown road conditions. The primary innovation is the finite-time smooth adaptive control algorithm, which is applied across the upper and lower control layers, as well as in the middle layer’s dynamic control allocation. In the upper layer, a novel smooth adaptive finite-time sliding mode controller is implemented using an integral fixed-time sliding variable to track the desired yaw rate. Similarly, the lower layer employs the same methodology to track the desired longitudinal slip. Additionally, the middle layer incorporates a finite-time smooth dynamic control allocation method to optimally distribute longitudinal slip among the tires, eliminating the need for tire-road friction estimation. The proposed framework offers several advantages, including reduced computational complexity, practical constraints handling and improved adaptability to varying road conditions and uncertainties. Simulations conducted on a validated 10-degree-of-freedom (10-DOF) vehicle model demonstrate the framework's superior performance in terms of tracking accuracy, smooth control signals, finite-time stability and adaptability to diverse conditions when compared to conventional methods.</p>

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Enhanced vehicle lateral stability under unknown road conditions using finite-time smooth adaptive sliding mode control

  • 期刊论文

  • 发表日期：

    2025年5月28日

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  • Vahid Behnamgol,
  • Mohammad Mirzaei,
  • Behnaz Sohani

摘要

This paper introduces a hierarchical three-layer adaptive control structure aimed at improving vehicle lateral stability under parametric uncertainties and unknown road conditions. The primary innovation is the finite-time smooth adaptive control algorithm, which is applied across the upper and lower control layers, as well as in the middle layer’s dynamic control allocation. In the upper layer, a novel smooth adaptive finite-time sliding mode controller is implemented using an integral fixed-time sliding variable to track the desired yaw rate. Similarly, the lower layer employs the same methodology to track the desired longitudinal slip. Additionally, the middle layer incorporates a finite-time smooth dynamic control allocation method to optimally distribute longitudinal slip among the tires, eliminating the need for tire-road friction estimation. The proposed framework offers several advantages, including reduced computational complexity, practical constraints handling and improved adaptability to varying road conditions and uncertainties. Simulations conducted on a validated 10-degree-of-freedom (10-DOF) vehicle model demonstrate the framework's superior performance in terms of tracking accuracy, smooth control signals, finite-time stability and adaptability to diverse conditions when compared to conventional methods.