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State Feedback Observer for Yaw Rate Based on the Nonlinear Vehicle Model

机译:基于非线性车辆模型的横摆率的状态反馈观察者

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Researching the estimating algorithm for the vehicle yaw rate is providing complement to the sensor measure and reference of the sensor diagnosis. If the estimating precision is good enough, the yaw rate sensor will be canceled and the cost of VDC system will be cut down. Based on the eight-DOF vehicle model and a modified Dugoff tire model which is simple and accurate, the estimation algorithm of vehicle yaw rate is proposed in this paper. The state feedback observer for yaw rate is designed and compared to the observer based on Kalman filter. The simulation results indicate that this algorithm can calculate vehicle yaw rate in real-time and the estimating precision is better than the Kalman filter in nonlinear condition. Therefore, the state feedback observer in this paper is proposing a low-cost and more practical idea for estimating the vehicle yaw rate on-line.
机译:研究车辆横摆率的估计算法提供了对传感器测量的补充和传感器诊断的参考。如果估计精度足够好,则将取消横摆率传感器,并且将减少VDC系统的成本。基于八截止车辆模型和简单准确的改进的Dugoff轮胎模型,本文提出了车辆横摆率的估计算法。横摆率的状态反馈观察者设计并与基于卡尔曼滤波器的观察者进行了设计。仿真结果表明,该算法可以实时计算车辆横摆率,并且估计精度优于非线性条件中的卡尔曼滤波器。因此,本文的状态反馈观察者正在提出估计车辆横摆率在线的低成本和更实际的想法。

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