A Tractable Fault Detection and Isolation Approach for Nonlinear Systems with Probabilistic Performance

P. Mohajerin Esfahani, John Lygeros

Research output: Contribution to journalArticleScientificpeer-review

32 Citations (Scopus)


This article presents a novel perspective along with a scalable methodology to design a fault detection and isolation (FDI) filter for high dimensional nonlinear systems. Previous approaches on FDI problems are either confined to linear systems or they are only applicable to low dimensional dynamics with specific structures. In contrast, shifting attention from the system dynamics to the disturbance inputs, we propose a relaxed design perspective to train a linear residual generator given some statistical information about the disturbance patterns. That is, we propose an optimization-based approach to robustify the filter with respect to finitely many signatures of the nonlinearity. We then invoke recent results in randomized optimization to provide theoretical guarantees for the performance of the proposed filer. Finally, motivated by a cyber-physical attack emanating from the vulnerabilities introduced by the interaction between IT infrastructure and power system, we deploy the developed theoretical results to detect such an intrusion before the functionality of the power system is disrupted.

Original languageEnglish
Article number7114245
Pages (from-to)633-647
JournalIEEE Transactions on Automatic Control
Issue number3
Publication statusPublished - 2016
Externally publishedYes

Bibliographical note

Geregistreerd op verzoek PM Esfahani vanwege aanvraag voor H2020 - programma. Geen TU Delft artikel door ontbreken affiliatie.


  • Differential-algebraic equation (DAE)
  • fault detection and isolation (FDI)


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