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Encyclopedia of Systems and Control pp 1–7Cite as

Stochastic Fault Detection

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Abstract

This entry describes the state-of-the-art and future perspectives on stochastic fault detection, namely, stochastic fault detection and diagnosis (FDD). Both model-based and data-driven FDD methods for stochastic signals and systems have been included, where the use of hypothesis testing, Kalman filtering, system estimation, principal component analysis (PCA), and stochastic distribution control has been discussed for the construction of effective FDD algorithms. Indeed, stochastic FDD constitute an important and integrated part in developing fault-tolerant controls (FTC) for guaranteed safe operation of control systems, of which increased penetration of random factors is inevitable nowadays.

This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the US Department of Energy. The US government retains, and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript or allow others to do so, for US government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan.)

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Author information

Authors and Affiliations

  1. Department of Electronic and Information Engineering, Bozhou University, Bozhou, Anhui, PR China

    Aiping Wang

  2. Energy and Transportation Science, Oak Ridge National Laboratory, Oak Ridge, TN, USA

    Hong Wang

  3. The University of Manchester, Manchester, UK

    Hong Wang

Authors
  1. Aiping Wang
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  2. Hong Wang
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Corresponding authors

Correspondence to Aiping Wang or Hong Wang .

Editor information

Editors and Affiliations

  1. Electrical and Computer Engineering, Boston University, Boston, MA, USA

    John Baillieul

  2. Automation and Control Solutions, Honeywell, Golden Valley, MN, USA

    Tariq Samad

Section Editor information

  1. South Kensington Campus, Electrical and Electronic Engineering, Imperial College, London, UK

    Thomas Parisini

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Wang, A., Wang, H. (2020). Stochastic Fault Detection. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5102-9_100098-1

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  • DOI: https://doi.org/10.1007/978-1-4471-5102-9_100098-1

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-5102-9

  • Online ISBN: 978-1-4471-5102-9

  • eBook Packages: Springer Reference EngineeringReference Module Computer Science and Engineering

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