International Journal of applied mathematics and computer science

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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

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.

fault diagnosis, large scale systems, multiple models