Fault diagnosis for unknown non-linear systems via neural networks and its comparisons and combinations with recursive least-squares based techniques

H. Wang, J. R. Noriega

Research output: Contribution to journalArticle

5 Citations (Scopus)
Original languageEnglish
Pages (from-to)261-278
Number of pages18
JournalProceedings of the Institution of Mechanical Engineers. Part I: Journal of Systems and Control Engineering
Volume215
Issue number3
DOIs
StatePublished - 1 Dec 2001
Externally publishedYes

Fingerprint

Failure analysis
Nonlinear systems
Neural networks
Actuators
Feedforward neural networks
Sensors

Keywords

  • Actuators and sensors
  • Fault detection and diagnosis
  • Least-squares estimation
  • Neural networks
  • Non-linear autoregressive moving-average model with exogenous input (NARMAX model)
  • Non-linear dynamic systems

Cite this

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keywords = "Actuators and sensors, Fault detection and diagnosis, Least-squares estimation, Neural networks, Non-linear autoregressive moving-average model with exogenous input (NARMAX model), Non-linear dynamic systems",
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