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Distributed Exponential State Estimation for Discrete-Time Linear Systems Over Jointly Connected Switching Networks

Tao Liu, Jie Huang

2023IEEE Transactions on Automatic Control21 citationsDOI

Abstract

The existing results on the distributed state estimation problem for discrete-time linear systems were obtained over connected static networks, or every-time connected switching networks by a two-time-scale design. This article further studies the same problem over jointly connected switching networks that can be disconnected at every time instant by a single-time-scale distributed design. Since the existing distributed designs critically rely on the connectedness assumption on the networks and thus may not apply to jointly connected switching networks, we manage to modify the local observers and develop a novel approach that makes use of the uniform complete observability property for a discrete-time time-varying system. Additionally, we establish two exponential stability results for two classes of discrete-time switched systems, which may be of independent interest.

Topics & Concepts

ObservabilityDiscrete time and continuous timeSocial connectednessComputer scienceStrongly connected componentState (computer science)Control theory (sociology)Exponential stabilityLinear systemStability (learning theory)Distributed computingMathematicsControl (management)AlgorithmApplied mathematicsMachine learningQuantum mechanicsPsychologyMathematical analysisPhysicsArtificial intelligencePsychotherapistStatisticsNonlinear systemStability and Control of Uncertain SystemsDistributed Control Multi-Agent SystemsStability and Controllability of Differential Equations
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