Distributed filtering for time-varying networked systems with sensor gain degradation and energy constraint: a centralized finite-time communication protocol scheme

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Bibliografiske detaljer
Udgivet i:Science China. Information Sciences vol. 61, no. 9 (Sep 2018), p. 092208
Hovedforfatter: Zhao, Ye
Andre forfattere: He, Xiao, Zhou, Donghua
Udgivet:
Springer Nature B.V.
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022 |a 1674-733X 
022 |a 1869-1919 
024 7 |a 10.1007/s11432-017-9256-3  |2 doi 
035 |a 2918593125 
045 2 |b d20180901  |b d20180930 
100 1 |a Zhao, Ye  |u Tsinghua University, National Laboratory for Information Science and Technology (TNList) and Department of Automation, Beijing, China (GRID:grid.12527.33) (ISNI:0000 0001 0662 3178) 
245 1 |a Distributed filtering for time-varying networked systems with sensor gain degradation and energy constraint: a centralized finite-time communication protocol scheme 
260 |b Springer Nature B.V.  |c Sep 2018 
513 |a Journal Article 
520 3 |a This paper focuses on the distributed filtering problem for a class of time-varying networked systems with sensor gain degradation and energy constrained communication protocol. To satisfy the requirement of power consumption and reduce the schedule computing complexity, centralized cyclic finite-time communication strategy optimization is taken into account. The networked system considered in this paper consists of spatially distributed sensors linked to their neighbor sensors, where each sensor node suffers from different gain degradation, and the transmission decisions of all the communication channels obey the centralized transmission schedule strategy identically. First, we present scattered communication action based on single-sensor transmission modeling with an energy constraint. Subsequently, an optimal communication protocol considering expected average error covariance is derived between the target system and each sensor node over the distributed sensor systems, based on a centralized finite-time scheme. Finally, by transforming the overall estimation error covariance of the systems at each sampling time into quadratic form, a conditionally unbiased least-square recursive distributed filtering technique over the networked system is designed at each sensor node. The system stability condition under such an optimal schedule is also accomplished with bounded covariance. A numerical example is provided to demonstrate the utility and effectiveness of the distributed filtering technique using the proposed optimized energy constrained communication protocol. 
653 |a Sensors 
653 |a Communication 
653 |a Distributed sensor systems 
653 |a Nodes 
653 |a Covariance 
653 |a Systems stability 
653 |a Constraint modelling 
653 |a Quadratic forms 
653 |a Degradation 
653 |a Power consumption 
653 |a Filtration 
653 |a Courthouses 
653 |a Schedules 
700 1 |a He, Xiao  |u Tsinghua University, National Laboratory for Information Science and Technology (TNList) and Department of Automation, Beijing, China (GRID:grid.12527.33) (ISNI:0000 0001 0662 3178) 
700 1 |a Zhou, Donghua  |u Shandong University of Science and Technology, College of Electrical Engineering and Automation, Qingdao, China (GRID:grid.412508.a) (ISNI:0000 0004 1799 3811); Tsinghua University, National Laboratory for Information Science and Technology (TNList) and Department of Automation, Beijing, China (GRID:grid.12527.33) (ISNI:0000 0001 0662 3178) 
773 0 |t Science China. Information Sciences  |g vol. 61, no. 9 (Sep 2018), p. 092208 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/2918593125/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/2918593125/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch