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Fuzzy Model-Based Fault Detection Approach for Nonlinear Control Processes

  • Xuejin Gao*
  • , Zeyang Qi
  • , Dong Zhao
  • , Huayun Han*
  • *Corresponding author for this work
  • Beijing University of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The key objective of this work is to deal with the fault detection issues for a general type of nonlinear control processes. Firstly, the approximation of the nonlinear process is studied based on a set of Takagi-Sugeno fuzzy systems. Then, a fuzzy controller based on an observer is present to achieve the stability of the nonlinear process, which also lays the basis for the construction of the image representations of the system and nominal system. With the image representations, the input and output signal errors are obtained, which can be used for the setting of the evaluation function. By handling a series of matrix inequalities, the threshold is designed, and a fault detection system for the nonlinear control process is realized with the decision logic. In the end, an illustration example is given to validate the obtained results.

Original languageEnglish
Title of host publicationProceedings - 2022 37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages242-247
Number of pages6
ISBN (Electronic)9781665465366
DOIs
StatePublished - 2022
Event37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022 - Beijing, China
Duration: 19 Nov 202220 Nov 2022

Publication series

NameProceedings - 2022 37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022

Conference

Conference37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022
Country/TerritoryChina
CityBeijing
Period19/11/2220/11/22

Keywords

  • fault detection
  • fuzzy observer-based controller
  • Image representation
  • Lyapunov function.
  • nonlinear control processes

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