**Reference:**

Zs. Lendek,
R. Babuska, and
B. De Schutter,
"Distributed Kalman filtering for multiagent systems," *Proceedings
of the European Control Conference 2007 (ECC'07)*, Kos, Greece,
pp. 2193-2200, July 2007.

**Abstract:**

For naturally distributed systems, such as multi-agent systems, the
construction and tuning of a centralized observer may be
computationally expensive or even intractable. An important class of
distributed systems can be represented as cascaded subsystems. For
this class of systems, observers may be designed separately for the
subsystems. If the subsystems are linear, the Kalman filter provides
an efficient means to estimate the states, so that it minimizes the
mean squared estimation error. Kalman-like filters may be used for the
whole system or the individual subsystems. In this paper, both a
theoretical comparison and simulation examples are presented. The
theoretical results show that the distributed observers, except for
special cases, do not minimize the overall error covariance, and so
the distributed observer system is suboptimal. However, in practice,
the performance achieved by the cascaded observers is comparable and
in certain cases outperforms that of the centralized one. Moreover, a
distributed observer system leads to increased modularity, reduced
complexity, and lower computational costs.

Corresponding technical report: pdf file (151 KB)

@inproceedings{LenBab:07-004,

author={{\relax Zs}. Lendek and R. Babu{\v{s}}ka and B. {D}e Schutter},

title={Distributed {Kalman} filtering for multiagent systems},

booktitle={Proceedings of the European Control Conference 2007 (ECC'07)},

address={Kos, Greece},

pages={2193--2200},

month=jul,

year={2007}

}

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