Consensus based overlapping decentralized estimation with missing observations and communication faults

Stanković, Srdjan; Stanković, Miloš S.; Stipanović, Dušan M.

doi:10.1016/j.automatica.2009.02.014

Cited by 165 publications

(60 citation statements)

References 32 publications

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“…The consensus problem was originally studied in management science (Degroot, 1974) and similar ideas were found in distributed computing (Tsitsiklis, 1984;Tsitsiklis et al, 1986). In recent years, some consensus algorithms were studied under various setups (Jadbabaie et al, 2003;Lin et al, 2004;2005;Olfati-Saber and Murray, 2004;Moreau, 2005;Ren and Beard, 2005;Hong et al, 2006;Cortés, 2008;Ren, 2008;Tahbaz-Salehi and Jadbabaie, 2008;Stanković et al, 2009;Tian and Liu, 2009;Nedic et al, 2010;Li et al, 2011;Cai and Ishii et al, 2012;Hendrickx and Tsitsiklis, 2013;Fanti et al, 2015).…”

Section: Consensusmentioning

confidence: 97%

Distributed coordination in multi-agent systems: a graph Laplacian perspective

Han

Lin

et al. 2015

Frontiers Inf Technol Electronic Eng

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This paper reviews some main results and progress in distributed multi-agent coordination from a graph Laplacian perspective. Distributed multi-agent coordination has been a very active subject studied extensively by the systems and control community in last decades, including distributed consensus, formation control, sensor localization, distributed optimization, etc. The aim of this paper is to provide both a comprehensive survey of existing literature in distributed multi-agent coordination and a new perspective in terms of graph Laplacian to categorize the fundamental mechanisms for distributed coordination. For different types of graph Laplacians, we summarize their inherent coordination features and specific research issues. This paper also highlights several promising research directions along with some open problems that are deemed important for future study.

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Section: Consensusmentioning

confidence: 97%

Distributed coordination in multi-agent systems: a graph Laplacian perspective

Han

Lin

et al. 2015

Frontiers Inf Technol Electronic Eng

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“…Assumption 2.5 is different from that given in many existing works [5,20,26,30], which rely on local observability, i. e., each agent is observable. Our work only need collective observable, which is much more suitable in applications.…”

Section: Formulationmentioning

confidence: 99%

“…Most of existing methods in distributed Kalman-filter-based estimation are based on consensus strategy [5,12,13,19,20,26,[28][29][30], which combine the consensus idea with state update based on the Kalman filter, called Kalman-consensus filter (KCF). For example, a distributed Kalman filter was developed in [19] using two identical consensus filters.…”

Section: Introductionmentioning

confidence: 99%

“…Since the optimal KCF is not scalable and needs all-to-all communication, a scalable suboptimal KCF was reported in [20]. Moreover, an algorithm for overlapping decentralized estimator was developed based on the consensus strategy in [26] assuming intermittent observations and communication faults. Additionally, some results were obtained for switching communication topologies [12,30] and nonlinear distributed filtering [10,11].…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, some results were obtained for switching communication topologies [12,30] and nonlinear distributed filtering [10,11]. However, most of the results [5,12,13,20,26,[28][29][30] required the local observ-DOI: 10.14736/kyb-2017-3-0545 able condition (i. e., each agent should be observable), which is not suitable in practical application. Different from the consensus approach to find the optimal Kalman filter gain and consensus gain in the distributed filtering, another kind of approach is to fuse the local estimate obtained by the Kalman filter [2,5,13], which can be treated as fusion-based distributed estimation.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Consensus-based state estimation for multi-agent systems with constraint information

Hu¹,

Qin²,

Li³

et al. 2017

Kybernetika

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Adaptive control and signal processing literature survey (No. 14)

2009

Adaptive Control & Signal

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In order to keep readers up to date, the journal will contain a list of recently published journal articles relevant to the fields of adaptive control and signal processing six times a year. This list is compiled from a wide range of journals. Please note that even though the list has been broadly categorized these classifications are by no means strict, and are there to assist the reader. Please also note that inclusion in the list is not an endorsement of a paper's quality. If you have any suggestions or comments, please gain of periodic linear switched systems: Fast switching behavior. IEEE Transactions on Automatic Control 2009; 54(7):1632-1637. Santarelli K, Dahleh M. L 2 gain stability of switched output feedback controllers for a class of LTI systems. IEEE Transactions on Automatic Control 2009; 54(7):1504-1514. Sun Z. Stabilizing switching design for switched linear systems: a state-feedback path-wise switching approach. Automatica 2009; 45(7):1708-1714. Wang J, Qu Z. Robust adaptive control of a class of nonlinearly parameterised time-varying uncertain systems. IET Control Theory and Applications 2009; 3(6):617-630. Xie D, Wang Q, Wu Y. Average dwell-time approach to L2 gain control synthesis of switched linear systems with time delay in detection of switching signal.

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Consensus based overlapping decentralized estimation with missing observations and communication faults

Cited by 165 publications

References 32 publications

Distributed coordination in multi-agent systems: a graph Laplacian perspective

Distributed coordination in multi-agent systems: a graph Laplacian perspective

Consensus-based state estimation for multi-agent systems with constraint information

Adaptive control and signal processing literature survey (No. 14)

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