文献类型：期刊文献

英文题名：Stochastic link activation for distributed filtering under sensor power constraint

作者：Yang, Wen[1];Yang, Chao[1];Shi, Hongbo[1];Shi, Ling[2];Chen, Guanrong[3]

机构：[1]East China Univ Sci & Technol, Key Lab Adv Control & Optimizat Chem Proc, Minist Educ, Shanghai, Peoples R China;[2]Hong Kong Univ Sci & Technol, Dept Elect & Comp Engn, Hong Kong, Hong Kong, Peoples R China;[3]City Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China

年份：2017

卷号：75

起止页码：109

外文期刊名：AUTOMATICA

收录：;EI(收录号：20164502985024);WOS:【SCI-EXPANDED(收录号:WOS:000391077800014)】；

基金：This work was supported in part by the National Natural Science Foundation of China under Grant (61573143, 61503139), the Hong Kong Research Grants Council under GRF Grant CityU 11208515, the RGC General Research Fund 16209114, the Innovation Program of Shanghai Municipal Education Commission under Grant No.14zz55, the Natural Science Foundation of Shanghai under Grant 16ZR1407400.

语种：英文

外文关键词：Distributed filtering; Sensor scheduling; Consensus; Convex optimization

摘要：We consider the problem of link activation for distributed estimation with power constraint. To satisfy the requirement of power consumption, we propose a stochastic link activation scheme, where each sensor equipped with a distributed estimator sends data to its neighboring sensors according to different probabilities. First, we design the optimal estimator gain of each sensor to minimize the state estimation error covariance. Then, we find an upper bound of the expected state estimation error covariance and provide a sufficient condition to guarantee the stability of the proposed estimator. Finally, we formulate the link activation problem as an optimization problem, and convert it to a convex optimization. (C) 2016 Elsevier Ltd. All rights reserved.