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Mode Detection and Fault Diagnosis in Hybrid Systems

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Fault Diagnosis of Dynamic Systems

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Abstract

This chapter primarily reviews methods for online monitoring, fault detection, and fault isolation of complex hybrid systems, such as automobiles [39], aircraft [13], and spacecraft [6, 12]. Hybrid systems mix continuous behaviors with discrete mode transitions that may be attributed to configuration changes in the system, or to simplifying assumptions, where complex nonlinearities are substituted by a sequence of simpler piecewise linear behaviors [33]. As a result, mathematical models that describe hybrid system behaviors are complex, and this makes the design of hybrid diagnosers a challenging task.

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Notes

  1. 1.

    https://faultdiagnosistoolbox.github.io/.

  2. 2.

    https://rosystemresiduals.github.io/.

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Author information

Authors and Affiliations

  1. Big Data Laboratory, R&D, Hitachi, Santa Clara, CA, USA

    Hamed Khorasgani

  2. Institute for Software Integrated Systems, Vanderbilt University, Nashville, TN, USA

    Gautam Biswas

Authors
  1. Hamed Khorasgani
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  2. Gautam Biswas
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Correspondence to Gautam Biswas .

Editor information

Editors and Affiliations

  1. Research Center for Supervision, Safety and Automatic Control (CS2AC), Universitat Politècnica de Catalunya (UPC), Terrassa, Spain

    Teresa Escobet

  2. Department of Computer Science, University of Valladolid, Segovia, Spain

    Anibal Bregon

  3. Department of Computer Science, University of Valladolid, Valladolid, Spain

    Belarmino Pulido

  4. Research Center for Supervision, Safety and Automatic Control (CS2AC), Universitat Politècnica de Catalunya (UPC), Terrassa, Spain

    Vicenç Puig

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Khorasgani, H., Biswas, G. (2019). Mode Detection and Fault Diagnosis in Hybrid Systems. In: Escobet, T., Bregon, A., Pulido, B., Puig, V. (eds) Fault Diagnosis of Dynamic Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-17728-7_13

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