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Design of a robust adaptive vehicle observer towards delayed and missing Vehicle Dynamics sensor signals by usage of Markov Chains

机译:使用马尔可夫链的鲁棒自适应车辆观测器针对延迟和丢失的车辆动力学传感器信号的设计

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As the influence and thereby the facilities for nowadays Vehicle Dynamics Control (VDC) systems increase by the expansion of actuators in vehicles, the measured vehicle dynamics get more and more relevant as they serve as basis for the controller. The common occurrence of delay or temporary absence of sensor signals raises new safety demands in order to guarantee passenger immunity. In this paper a new method for the handling of delayed and missing vehicle dynamics sensor signals by use of Markov Chains is introduced. The performance of this method in combination with a vehicle observer based on Extended Kalman Filter (EKF) technique is validated by simulation. The results are provided to illustrate the performance of this concept. Here the missing and delayed measurements are realized by a binary switching sequence.
机译:随着车辆执行器的扩展,当今影响车辆动态控制(VDC)系统的设施以及由此而增加的设备,所测得的车辆动态性越来越重要,因为它们是控制器的基础。为了保证乘客的免疫力,通常会出现延迟或暂时缺少传感器信号的情况,提出了新的安全要求。本文介绍了一种利用马尔可夫链处理延迟和丢失的车辆动力学传感器信号的新方法。通过仿真验证了该方法与基于扩展卡尔曼滤波(EKF)技术的车辆观察器相结合的性能。提供结果以说明此概念的性能。在这里,丢失和延迟的测量是通过二进制切换序列实现的。

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