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Distributed Estimation Recovery Under Sensor Failure
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DOI：10.1109/LSP.2017.2749265.png)
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Abstract
En 中文
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 alpha and beta sensors. We propose polynomial-order algorithms to find equivalent state nodes in graph representation of the system to recover for distributed observability. The polynomialorder solution is particularly significant for large-scale systems.
Keywords:
Contraction
distributed estimation
observability
sensor failure
strongly connected component (SCC)
system digraph
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