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Higher-order sliding mode observer for estimation of tyre friction in ground vehicles

机译:用于评估地面车辆轮胎摩擦的高阶滑模观察器

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摘要

The estimation of friction coefficient for a vehicle when it traverses on different surfaces has been an important issue. In this work, the longitudinal vehicle dynamics, the torsional tyre dynamics and the non-linear LuGre friction dynamics are integrated to model the quarter vehicle dynamics. The road adhesion coefficient in the vehicle dynamics is unknown and varies with the contact surface. To address this issue, the authors consider a class of non-linear uncertain systems that covers the vehicle dynamics and develop a higher-order sliding mode observer based on supertwisting algorithm for state and unknown input estimations. Under Lipschitz conditions for the non-linear functions, the convergence of the estimation error is established. By estimating the road adhesion coefficient, the coefficient of friction can be estimated. Simulation results demonstrate the effectiveness of the proposed observer for state and unknown input estimation.
机译:车辆在不同表面上行驶时的摩擦系数的估计是一个重要的问题。在这项工作中,纵向车辆动力学,扭转轮胎动力学和非线性LuGre摩擦动力学被集成以模拟四分之一车辆动力学。车辆动力学中的道路附着系数未知,并且会随接触表面而变化。为了解决这个问题,作者考虑了一类涵盖车辆动力学的非线性不确定系统,并基于状态和未知输入估计的超扭曲算法开发了一种高阶滑模观测器。在非线性函数的Lipschitz条件下,建立了估计误差的收敛性。通过估计道路附着系数,可以估计摩擦系数。仿真结果证明了所提出的观测器对于状态和未知输入估计的有效性。

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