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Distributed estimation recovery under sensor failure

Doostmohammadian, M ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/LSP.2017.2749265
  3. Abstract:
  4. Single-time-scale distributed estimation of dynamic systems via a network of sensors/estimators is addressed in this letter. In single-time-scale distributed estimation, the two fusion steps, consensus and measurement exchange, are implemented only once, in contrast to, e.g., a large number of consensus iterations at every step of the system dynamics. We particularly discuss the problem of failure in the sensor/estimator network and how to recover for distributed estimation by adding new sensor measurements from equivalent states. We separately discuss the recovery for two types of sensors, namely α and β sensors. We propose polynomial-order algorithms to find equivalent state nodes in graph representation of the system to recover for distributed observability. The polynomial-order solution is particularly significant for large-scale systems. © 1994-2012 IEEE
  5. Keywords:
  6. Contraction ; Strongly connected component (SCC) ; Estimation ; Graph theory ; Large scale systems ; Observability ; Polynomials ; Recovery ; Shrinkage ; System theory ; Telecommunication networks ; DH-Hemts ; Distributed estimation ; Noise measurements ; Sensor failure ; System digraph ; System dynamics ; Computer system recovery
  7. Source: IEEE Signal Processing Letters ; Volume 24, Issue 10 , 2017 , Pages 1532-1536 ; 10709908 (ISSN)
  8. URL: https://ieeexplore.ieee.org/document/8025781