Open AccessDistributed average filtering for sensor networks with sensor saturation
Author(s) -
Zhang Hao,
Yan Huaicheng,
Yang Fuwen,
Chen Qijun
Publication year - 2013
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2012.0558
Subject(s) - ellipsoid , bounded function , estimator , control theory (sociology) , filtering problem , wireless sensor network , brooks–iyengar algorithm , set (abstract data type) , state (computer science) , controller (irrigation) , computer science , mathematics , algorithm , filter (signal processing) , filter design , control (management) , artificial intelligence , statistics , key distribution in wireless sensor networks , mathematical analysis , biology , telecommunications , agronomy , wireless , computer vision , programming language , physics , wireless network , computer network , astronomy
This study addresses the distributed average set‐membership filtering of spatially varying processes using sensor networks. The system under consideration contains sensor saturation in the presence of unknown‐but‐bounded process and measurement noise in the sensor network. The so‐called distributed average set‐membership filtering is defined to quantify bounded consensus regarding the estimation error. A sufficient condition for distributed average set‐membership filtering parameter design is established in terms of a set of time‐varying linear matrix inequalities. A recursive algorithm is developed for computing the estimator, controller gains and the ellipsoid that guarantees to contain the true state. Simulation results are provided to demonstrate the effectiveness of the proposed method.