Decentralized Kalman filter comparison for distributed-parameter systems: A case study for a 1D heat conduction process

Z. Hidayat*, R. Babuška, B. De Schutter, A. Núñez

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

22 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings of 2011 IEEE 16th Conference on Emerging Technologies and Factory Automation, ETFA 2011
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 IEEE 16th Conference on Emerging Technologies and Factory Automation, ETFA 2011 - Toulouse, France
Duration: 5 Sept 20119 Sept 2011

Publication series

NameIEEE International Conference on Emerging Technologies and Factory Automation, ETFA

Conference

Conference2011 IEEE 16th Conference on Emerging Technologies and Factory Automation, ETFA 2011
Country/TerritoryFrance
CityToulouse
Period5/09/119/09/11

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