A novel cyber physical method is proposed and experimentally verified for reliable distributed estimation of vehicle longitudinal velocity, robustly to road friction condition variations. In this method, the vehicle speed estimated at each of the four corners of the vehicle, using a linear parameter-varying observer in the physical layer, and speed data measured by a conventional low-cost GPS are incorporated in a distributed structure (in the cyber layer) to enhance the reliability of the estimate. The method minimizes a cost function quantizing the effect of disturbances on each corner's estimation and adversaries due to occasional GPS signal drops. A fault-tolerant estimation policy is integrated to deal with large deviations in corner estimations, which have unexpectedly high levels of confidence. The main advantages of the proposed method are increased reliability on various road surface conditions and robustness to faults, as confirmed by road tests. Several experimental tests, including lane change and low-excitation maneuvers, with various powertrain configurations on dry and slippery roads demonstrate the efficiency of the algorithm.

中文翻译：

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车辆状态估计的容错共识：一种网络物理方法


提出了一种新颖的网络物理方法并进行了实验验证，用于可靠地分布式估计车辆纵向速度，对道路摩擦条件变化具有鲁棒性。在该方法中，使用物理层中的线性参数变化观测器估计车辆四个角的车速，并将传统低成本 GPS 测量的速度数据合并到分布式结构中（在网络层）以增强估计的可靠性。该方法最小化了成本函数，该函数量化了由于偶尔的 GPS 信号下降而对每个角点的估计和对手的干扰的影响。集成了容错估计策略来处理角点估计中的大偏差，这些偏差具有意想不到的高置信度。道路测试证实，该方法的主要优点是提高了各种路面条件下的可靠性和对故障的鲁棒性。在干燥和湿滑的道路上使用各种动力总成配置进行的多项实验测试（包括变道和低励磁操作）证明了该算法的效率。