Reference
Z. Hidayat, R. Babuška, B. De Schutter, and A. Núñez,
"Decentralized Kalman filter comparison for distributed-parameter systems: A
case study for a 1D heat conduction process,"
Proceedings of
the 16th IEEE International Conference on Emerging Technologies and Factory
Automation (ETFA'2011), Toulouse, France, 8 pp., Sept. 2011.
Abstract
In this paper we compare four methods for decentralized Kalman filtering for
distributed-parameter systems, which after spatial and temporal discretization,
result in large-scale linear discrete-time systems. These methods are: parallel
information filter, distributed information filter, distributed Kalman filter
with consensus filter, and distributed Kalman filter with weighted averaging.
These filters are suitable for sensor networks, where the sensor nodes perform
not only sensing and computations, but also communicate estimates among each
other. We consider an application of sensor networks to a heat conduction
process. The performance of the decentralized filters is evaluated and compared
to the centralized Kalman filter.
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BibTeX
@inproceedings{HidBab:11-028,
author = {Hidayat, Zul and Babu{\v{s}}ka, Robert and De Schutter, Bart
and N{\'{u}}{\~{n}}ez, Alfredo},
title = {Decentralized {Kalman} Filter Comparison for
Distributed-Parameter Systems: {A} Case Study for a {1D} Heat
Conduction Process},
booktitle = {Proceedings of the 16th IEEE International Conference on
Emerging Technologies and Factory Automation (ETFA'2011)},
address = {Toulouse, France},
month = sep,
year = {2011}
}