Distributed robust filtering with H∞ consensus of estimates

The paper addresses a problem of design of distributed robust filters using the recent vector dissipativity theory. The main result is a sufficient condition which guarantees a suboptimal H∞ level of disagreement of estimates in a network of filters. It involves solving a convex optimization/feasibi...

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Veröffentlicht in:Automatica (Oxford) Jg. 47; H. 1; S. 1 - 13
1. Verfasser: Ugrinovskii, V.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Kidlington Elsevier Ltd 01.01.2011
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ISSN:0005-1098, 1873-2836
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Abstract The paper addresses a problem of design of distributed robust filters using the recent vector dissipativity theory. The main result is a sufficient condition which guarantees a suboptimal H∞ level of disagreement of estimates in a network of filters. It involves solving a convex optimization/feasibility problem subject to LMI constraints. The special case of balanced interconnection graphs is also considered. A gradient descent type algorithm is presented which allows the nodes to compute their estimator parameters in a decentralized manner. The proposed approach is applied to the problem of observer-based robust synchronization of a nonlinear network to an isolated node.
AbstractList The paper addresses a problem of design of distributed robust filters using the recent vector dissipativity theory. The main result is a sufficient condition which guarantees a suboptimal H∞ level of disagreement of estimates in a network of filters. It involves solving a convex optimization/feasibility problem subject to LMI constraints. The special case of balanced interconnection graphs is also considered. A gradient descent type algorithm is presented which allows the nodes to compute their estimator parameters in a decentralized manner. The proposed approach is applied to the problem of observer-based robust synchronization of a nonlinear network to an isolated node.
Author Ugrinovskii, V.
Author_xml – sequence: 1
  givenname: V.
  surname: Ugrinovskii
  fullname: Ugrinovskii, V.
  email: v.ugrinovskii@gmail.com, v.ougrinovski@adfa.edu.au
  organization: School of Engineering and IT, University of NSW at the Australian Defence Force Academy, Canberra, ACT, 2600, Australia
BackLink http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=23753549$$DView record in Pascal Francis
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ISSN 0005-1098
IngestDate Mon Jul 21 09:15:35 EDT 2025
Sat Nov 29 01:49:10 EST 2025
Tue Nov 18 22:43:14 EST 2025
Fri Feb 23 02:14:12 EST 2024
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Issue 1
Keywords Gradient algorithms
Vector dissipativity
Large-scale systems
Distributed robust filtering
Consensus
Vector Lyapunov functions
Convex programming
Gradient descent
Hamiltonian graph
Observer
Linear matrix inequality
System identification
Mathematical programming
Large scale system
Gradient
H infinite control
Distributed system
Synchronization
Search algorithm
Robust control
Filter
Dissipative system
Descent method
Feasibility
Sensor array
Lyapunov function
Language English
License CC BY 4.0
LinkModel OpenURL
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PublicationTitle Automatica (Oxford)
PublicationYear 2011
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Elsevier
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Snippet The paper addresses a problem of design of distributed robust filters using the recent vector dissipativity theory. The main result is a sufficient condition...
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SubjectTerms Applied sciences
Computer science; control theory; systems
Computer systems and distributed systems. User interface
Consensus
Control theory. Systems
Distributed robust filtering
Exact sciences and technology
Gradient algorithms
Large-scale systems
Modelling and identification
Software
Vector dissipativity
Vector Lyapunov functions
Title Distributed robust filtering with H∞ consensus of estimates
URI https://dx.doi.org/10.1016/j.automatica.2010.10.002
Volume 47
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