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Paper details
Number 2 - June 2020
Volume 30 - 2020
Decentralized and distributed active fault diagnosis: Multiple model estimation algorithms
Ondřej Straka, Ivo Punčochář
Abstract
The paper focuses on active fault diagnosis (AFD) of large scale systems. The multiple model framework is considered
and two architectures are treated: the decentralized and the distributed one. An essential part of the AFD algorithm is
state estimation, which must be supplemented with a mechanism to achieve feasible implementation in the multiple model
framework. In the paper, the generalized pseudo Bayes and interacting multiple model estimation algorithms are considered.
They are reformulated for a given model of a large scale system. Performance of both AFD architectures is analyzed for
different combinations of multiple model estimation algorithms using a numerical example.
Keywords
fault diagnosis, large scale systems, multiple models