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Adaptive SMO-Based Fault Estimation for Markov Jump Systems with Simultaneous Additive and Multiplicative Actuator Faults

  • Hongyan Yang
  • , Hao Luo
  • , Okyay Kaynak
  • , Shen Yin*
  • *Corresponding author for this work
  • Harbin Institute of Technology
  • Bogazici University

Research output: Contribution to journalArticlepeer-review

Abstract

This article studies the problem of fault reconstruction, disturbance estimation, and state estimation for Markovian jump systems (MJSs) with simultaneous additive and multiplicative actuator faults. First, we rewrite the original Markov jump linear systems into an extended form, where the extended vector is composed of an actuator fault vector, a disturbance vector, and a state vector. Then, by proposing a continuous adaptive sliding-mode observer for the extended-form MJSs, the state estimation, actuator fault reconstruction, and disturbance estimation can be achieved. Moreover, the stochastic stability of the overall error plant can be guaranteed. Finally, a simulation example is employed to illustrate the effectiveness of our theoretical results.

Original languageEnglish
Article number8964280
Pages (from-to)607-616
Number of pages10
JournalIEEE Systems Journal
Volume15
Issue number1
DOIs
StatePublished - Mar 2021

Keywords

  • Adaptive observer
  • Markovian jump systems (MJSs)
  • additive actuator faults
  • fault detection
  • multiplicative actuator faults
  • sliding-mode observer (SMO)

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