Fault Diagnosis in Dynamical Systems
Geometric Interpretation and Tractable Algorithms
Mohammad Amin Sheikhi (TU Delft - Team Tamas Keviczky)
Gabriel de Albuquerque Gleizer (TU Delft - Team Gabriel Gleizer)
Tamás Keviczky (TU Delft - Team Tamas Keviczky)
Peyman Mohajerin Esfahani (TU Delft - Team Peyman Mohajerin Esfahani, University of Toronto)
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Abstract
This survey reviews recent developments in fault diagnosis for both linear and nonlinear dynamical systems, covering model-based and data-driven approaches as well as passive and active detection and estimation methods. A central focus is placed on the geometric interpretation of diagnosis filters and their connection to the concept of behavioral sets, providing an intuitive view of their performance. We also review optimization-based techniques that enhance the robustness of linear filters when applied to nonlinear or uncertain systems. Furthermore, we point out recent progress in active fault diagnosis, where input design plays a key role in improving detectability and estimation accuracy. To bridge theory and practice, we include a set of real-world industrial applications that demonstrate the implementation and effectiveness of these methods in realistic settings.
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