A Structural Approach to Sensor Placement based on Symbolic Compilation of the Model
In the present paper we address the problem of computing the Minimal Additional Sensor Sets (MASS) that guarantee a desired level of diagnostic discrimination for a system.
The main contribution of this paper is the extension and the adaptation of techniques based on the symbolic compilation of qualitative system models to a structural approach suitable for the computation of MASS for component-oriented models consisting of sets of numerical equations. In this respect, the paper can be viewed as a bridge across the AI approaches to model-based sensor placement and the Fault Detection and Isolation approaches developed by the Automatic Control community. We show that the resulting method exploits the symbolic compilation techniques not only as a way to provide computational savings (including some theoretical guarantees on the computational complexity), but it also exhibits interesting new features, most notably the handling of multiple faults.
KeywordsExogenous Variable Endogenous Variable Relational Algebra Minimum Cardinality Domain Theory
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