Observer-based neural adaptive fixed-time tracking control for multi-input multi-output nonlinear systems with actuator faults

Xiaona Song, Peng Sun, Choon Ki Ahn, Shuai Song

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


This study developed a new strategy for adaptive fixed-time output feedback control of multi-input multi-output (MIMO) nonlinear systems involving unmeasurable external disturbances and actuator faults. Two actuator faults, loss of effectiveness and lock-in-place were simultaneously considered. Furthermore, a composite observer was used in MIMO systems to estimate unmeasurable states and external disturbances simultaneously, and radial basis function neural networks were employed to identify unknown internal nonlinearities. Additionally, the command-filtered backstepping approach was applied to avoid tedious analytic calculations of the backstepping framework, and a compensation item was constructed to attenuate the filter error. A fault-tolerant controller was developed to ensure that the overall states of the controlled system were practically fixed-time bounded while the tracking error was regulated to the equilibrium region having a fixed-time convergence ratio. Illustrative studies showed the validity and practicability of the proposed theory.

Original languageEnglish
Pages (from-to)6849-6872
Number of pages24
JournalInternational Journal of Robust and Nonlinear Control
Issue number12
Publication statusPublished - 2023 Aug

Bibliographical note

Publisher Copyright:
© 2023 John Wiley & Sons Ltd.


  • actuator fault
  • command filter backstepping
  • composite observer
  • fixed-time stability
  • multi-input multi-output nonlinear system
  • neural adaptive control

ASJC Scopus subject areas

  • Control and Systems Engineering
  • General Chemical Engineering
  • Biomedical Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering


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