Distributed H∞ filtering over sensor networks with heterogeneous Markovian coupling intercommunication delays. Issue 1 (1st January 2015)

• Record Type: Journal Article
• Authors: Ge, Xiaohua; Han, Qing‐Long; Jiang, Xiefu
• Is Part Of: IET control theory & applications. Volume 9:Issue 1(2015)
• Page Start: 82
• Page End: 90
• Publication Date: 2015-01-01
• Subjects: H∞ filters -- filtering theory -- distributed sensors -- delays -- Markov processes -- asymptotic stability -- linear systems -- continuous time systems -- distributed parameter systems; distributed H∞ filtering -- sensor networks -- heterogeneous Markovian coupling intercommunication delays -- continuous‐time linear systems -- sensing network -- communication network -- neighbouring sensor nodes -- directed graph -- heterogeneous random coupling delays -- Markov process -- refined two‐step decoupling technique -- resultant filtering error system -- mean square exponential stability -- weighting average H∞ performance; Control theory -- Periodicals; Automatic control -- Periodicals; 629.8312
• DOI: 10.1049/iet-cta.2014.0006
• Languages: English
• ISSNs: 1751-8644

Abstract

Abstract : This study is concerned with distributed H ∞ filtering for continuous‐time linear systems over sensor networks with heterogeneous Markovian coupling intercommunication delays. The set of sensor nodes forms a sensing and communication network whose topology is modelled by a directed graph that describes the measurement exchanged among neighbouring sensor nodes. Heterogeneous random coupling delays modelled by a Markov process are considered in the intercommunication between interacting sensor nodes. A refined two‐step decoupling technique is presented to deal with the complicated coupling of exchanged measurement in the presence of the delays. A sufficient condition on the existence of desired distributed H ∞ filters is derived such that the resultant filtering error system is mean square exponentially stable with prescribed weighting average H ∞ performance. Two illustrative examples are given to show the effectiveness of the proposed results.