Fault Sensor Detection and Estimation based on LPV Observer for Vehicle Lateral Dynamics

I. Alaridh, A. Aitouche, A. Zemouche
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Abstract

This paper deals with a fault sensor detection and estimation based on Unknown Input Observer (UIO) for vehicle lateral dynamics. The vehicle lateral dynamics is represented by a fourth degree of freedom model. This nonlinear model is transformed into linear parameter varying model where the longitudinal velocity is considered as parameter varying. Then, an Unknown Input Observer is designed in order to reconstruct the state variables in presence of sensor faults.Based on Lyapunov theory, the observer gains are computed by Linear Matrix Inequalities. The approach can discriminate sensor faults from disturbances. Simulation results are given to show the effectiveness of the proposed approach to detect sensor faults subject to disturbances.
基于LPV观测器的车辆横向动力学故障传感器检测与估计
研究了一种基于未知输入观测器的车辆横向动力学故障传感器检测与估计方法。车辆横向动力学用四自由度模型表示。将该非线性模型转化为线性参数变化模型,将纵向速度视为参数变化模型。然后,设计了未知输入观测器,以便在传感器出现故障时重构状态变量。基于李雅普诺夫理论,利用线性矩阵不等式计算观测器增益。该方法可以区分传感器故障和干扰。仿真结果表明了该方法在检测受干扰的传感器故障时的有效性。
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