Encyclopedia of Systems and Control

Living Edition
| Editors: John Baillieul, Tariq Samad

Stochastic Fault Detection

  • Aiping WangEmail author
  • Hong WangEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4471-5102-9_100098-1
  • 12 Downloads

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.

Keywords

Hypothesis testing Fault detection and diagnosis (FDD) System identification Multivariable statistics Stochastic distribution controls 
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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2020

Authors and Affiliations

  1. 1.Department of Electronic and Information EngineeringBozhou UniversityBozhouPR China
  2. 2.Energy and Transportation ScienceOak Ridge National LaboratoryOak RidgeUSA
  3. 3.The University of ManchesterManchesterUK

Section editors and affiliations

  • Thomas Parisini
    • 1
  1. 1.South Kensington CampusElectrical and Electronic Engineering, Imperial CollegeLondonUK