Skip to main navigation Skip to search Skip to main content

Fault-Tolerant Stochastic Sampled-Data Fuzzy Control for Nonlinear Delayed Parabolic PDE Systems

  • Qian-Qian Li
  • , Zi-Peng Wang*
  • , Tingwen Huang
  • , Huai-Ning Wu
  • , Han-Xiong Li
  • , Junfei Qiao
  • *Corresponding author for this work

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Abstract

    For nonlinear delayed parabolic partial differential equation (PDE) systems, this paper addresses fault-tolerant stochastic sampled-data (SD) fuzzy control under spatially point measurements (SPMs). Initially, a T–S fuzzy PDE model is given to accurately describe the nonlinear delayed parabolic PDE system. Secondly, in consideration of possible actuator failure, a fault-tolerant SD fuzzy controller with stochastic sampling under SPMs is designed for nonlinear delayed parabolic PDE system, where two sampling periods are considered whose occurrence probabilities are given constants and satisfy the Bernoulli distribution. Then, by constructing a novel time-dependent Lyapunov functional, sufficient conditions that guarantee the mean square exponential stability of closed-loop delayed PDE system are obtained based on linear matrix inequalities (LMIs). Lastly, three examples are given to illustrate the designed approach. © 2023 IEEE.
    Original languageEnglish
    Pages (from-to)2679-2693
    Number of pages15
    JournalIEEE Transactions on Fuzzy Systems
    Volume31
    Issue number8
    Online published16 Jan 2023
    DOIs
    Publication statusPublished - Aug 2023

    Research Keywords

    • Actuators
    • Fault tolerance
    • Fault tolerant systems
    • fault-tolerant control
    • Fuzzy control
    • Mathematical models
    • Nonlinear delayed parabolic PDE system
    • spatially point measurements
    • Stochastic processes
    • stochastic sampled-data control
    • Upper bound

    Fingerprint

    Dive into the research topics of 'Fault-Tolerant Stochastic Sampled-Data Fuzzy Control for Nonlinear Delayed Parabolic PDE Systems'. Together they form a unique fingerprint.

    Cite this