Diagnosability Analysis Considering Causal Interpretations for Differential Constraints
This work is focused on structural approaches to studying
diagnosability properties given a system model taking into account,
both simultaneously or separately, integral and differential causal
interpretations for differential constraints. We develop a model
characterization and corresponding algorithms, for studying system
diagnosability using a structural decomposition that avoids generating
the full set of system ARRs. Simultaneous application of integral and
differential causal interpretations for differential constraints
results in a mixed causality interpretation for the system. The
added power of mixed causality is demonstrated using a case
study. Finally, we summarize our work and provide a discussion of the
advantages of mixed causality over just derivative or just integral
causality.
Erik Frisk, Anibal Bregon, Jan Åslund, Mattias Krysander, Belarmino Pulido and Gautam Biswas
21st International Workshop on Principles of Diagnosis (DX-10),
2010
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