文献类型：期刊文献

英文题名：Sensor Scheduling for Remote State Estimation with Limited Communication Resources: A Time- and Event-Triggered Hybrid Approach

作者：Ni, Yuqing[1];Liu, Xiaochen[2];Yang, Chao[3]

机构：[1]Jiangnan Univ, Sch Internet Things Engn, Key Lab Adv Proc Control Light Ind, Minist Educ, Wuxi 214122, Peoples R China;[2]Harvard Med Sch, Massachusetts Gen Hosp, Athinoula A Martinos Ctr Biomed Imaging, Dept Radiol, Boston, MA 02114 USA;[3]East China Univ Sci & Technol, Dept Automat, Key Lab Smart Mfg Energy Chem Proc, Minist Educ, Shanghai 200237, Peoples R China

年份：2023

卷号：23

期号：21

外文期刊名：SENSORS

收录：;EI(收录号：20234615061709);WOS:【SCI-EXPANDED(收录号:WOS:001100299500001)】；

基金：This research was funded by the National Natural Science Foundation of China under Grant 62303196, 62336005, and 61973163, the Fundamental Research Funds for the Central Universities,JUSRP122048, the Basic Research Funds of Wuxi Taihu Light Project under Grant K20221005, and the 111 Project under Grant B23008.

语种：英文

外文关键词：remote state estimation; Kalman filtering; sensor scheduling; stochastic event trigger; hybrid scheduling

摘要：This paper proposes a time- and event-triggered hybrid scheduling for remote state estimation with limited communication resources. A smart sensor observes a physical process and decides whether to send the local state estimate to a remote estimator via a wireless communication channel; the estimator computes the state estimate of the process according to the received data packets and the known scheduling mechanism. Based on the existing optimal time-triggered scheduling, we employ a stochastic event trigger to save precious communication chances and further improve the estimation performance. The minimum mean-squared error (MMSE) state estimate is derived since the Gaussian property is preserved. The estimation performance upper bound and communication rate are analyzed. The main results are illustrated by numerical examples.