Readings in model-based diagnosis
Readings in model-based diagnosis
Diagnosis and Fault-Tolerant Control
Diagnosis and Fault-Tolerant Control
Improving robustness in consistency-based diagnosis using possible conflicts
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Diagnosis of Complex Systems: Bridging the Methodologies of the FDI and DX Communities
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Possible conflicts: a compilation technique for consistency-based diagnosis
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An Efficient Algorithm for Finding Minimal Overconstrained Subsystems for Model-Based Diagnosis
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
An event-based distributed diagnosis framework using structural model decomposition
Artificial Intelligence
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Diagnosis of real world problems demands the integration of different techniques from several research fields. In Model-based Diagnosis, both Artificial Intelligence and Control Theory communities have provided different but complementary approaches. Recent works, known as BRIDGE proposal, provided a common framework for the integration of techniques for static systems. This work proposes the extension of the BRIDGE framework for a specific class of dynamic systems, thus analyzing the influence of dynamic constraints in the behavior estimation capabilities for two Model-based Diagnosis techniques: Possible Conflicts and Analytical Redundancy Relations obtained through structural analysis. Results show the strong similarities between them, and provide new ways for integration of techniques from both areas. Additionally, algorithms computing Possible Conflicts provide the implicit structural model for state observer design with no extra knowledge added in the model. Results on a case study are provided, then compared and discussed against existing proposals.