Structural analysis for the diagnosis of distributed systems

Carlos Gustavo Pérez Zuniga 1
1 LAAS-DISCO - Équipe DIagnostic, Supervision et COnduite
LAAS - Laboratoire d'analyse et d'architecture des systèmes [Toulouse]
Abstract : This thesis focuses on fault detection and isolation. Among the different methods to generate diagnosis tests by taking advantage of analytical redundancy, this thesis adopts the approach based on analytical redundancy relations (ARRs). Given a model of the system in the form of a set of differential equations, ARRs are relations that are obtained from the model by eliminating non measured variables. This can be performed in an analytical framework using elimination theory. Another way of doing this is to use structural analysis. Structural analysis is based on a structural abstraction of the model that only retains a representation of which variables are involved in which equations. Despite the rusticity of the abstract model, structural analysis provides a set of powerful tools, relying on graph theory, to analyze and infer information about the system. Interestingly, it applies indifferently to linear or nonlinear systems. This thesis proposes efficient algorithms based on structural analysis for the diagnosis of decentralized and distributed continuous systems as well as for the choice of an optimal set of tests. These algorithms were tested on two industrial case studies.
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Automatic. Institut National des Sciences Appliquées de Toulouse, 2017. English
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Carlos Gustavo Pérez Zuniga. Structural analysis for the diagnosis of distributed systems. Automatic. Institut National des Sciences Appliquées de Toulouse, 2017. English. 〈tel-01631550〉



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