Study of a Robust Federated Filtering Algorithm Based on Fault Factor Function
Study of a Robust Federated Filtering Algorithm Based on Fault Factor Function
复制标题
DOI：
--
复制
发表时间：
2006
期刊：
影响因子：
--
通讯作者：
Wu Xun-zhong;Zhou Jun
中科院分区：
文献类型：
--
作者：
Wu Xun-zhong;Zhou Jun
本文首先提出了一种改进的基于状态传播算子的具有高故障检测灵敏度的移动残差检验方法。然后定义故障因子函数，实现联邦滤波器的系统信息共享。通过分析传感器故障对具有不同信息系数的优良子系统的影响，提出了一种自适应信息共享算法，通过增强优良子系统的鲁棒性来提高联邦滤波器的恢复能力。该算法根据故障因素自适应地调整信息共享系数，通过全局融合复位减少故障传感器对好传感器的污染。因此，在故障隔离之后，仍然存在于良好子系统中的故障信息在重新生成的联邦填充器中只会持续很短的时间。仿真结果表明了该方法的有效性。
This paper firstly proposes an improved moving residual test with high fault detection sensitivity based on the state propagator for the federated filter. Then the fault factor function is defined to share the system information of the federated filter. With an analysis of the sensor failure's influence on the good subsystems with different information coefficients, an adaptive information sharing algorithm is presented to improve the recovery capability of the federated filter by heightening the robustness of the good subsystems. By this algorithm, the information sharing coefficients are adaptively adjusted according to the fault factors, and the faulty sensor's contamination on the good sensors via the global fusion reset is reduced. So after fault isolation, the fault information still in good subsystems will only last a very short time in the regenerated federated filler. The simulation shows this method is effective.