A Modified Data-driven Distributed Information-Weighted Kalman Consensus Filtering with Switching Topology and Packet Loss

被引：1

作者：

Ji, Honghai ^{[1
]}

Wu, Yuxin ^{[1
]}

Liu, Shida ^{[1
]}

Wang, Li ^{[1
]}

Fan, Lingling ^{[2
]}

Xiong, Shuangshuang ^{[2
]}

机构：

[1] North China Univ Technol, Dept Elect & Control Engn, Beijing 100144, Peoples R China

[2] Beijing Informat Sci & Technol Univ, Sch Automat, Beijing 100096, Peoples R China

来源：

2023 IEEE 12TH DATA DRIVEN CONTROL AND LEARNING SYSTEMS CONFERENCE, DDCLS | 2023年

关键词：

Data-driven Filtering; distributed state estimation; sensor networks; packet loss; switching topologies;

D O I：

10.1109/DDCLS58216.2023.10166520

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper is concerned with distributed state estimation problem over sensor networks with uncertainty in communication networks. Because of the instability of communication in real systems, it is meaningful to consider packet loss and topology change. Thus, based on Kalman consensus filtering algorithm and Data-driven filtering technique, we proposed a modified Data-driven Distributed information-weighted Kalman Consensus Filter to estimate the state. Finally, the effectiveness of the designed algorithm is validated by a simulation example.

引用

页码：1221 / 1226

页数：6

共 13 条

[1] Data-Driven Distributed Information-Weighted Consensus Filtering in Discrete-Time Sensor Networks With Switching Topologies
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