4.8 Article

Finite-Time Control for Multiple Time-Delayed Fuzzy Large-Scale Systems Against State and Input Constraints

期刊

IEEE TRANSACTIONS ON FUZZY SYSTEMS
卷 30, 期 12, 页码 5390-5404

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2022.3176933

关键词

Finite-time boundedness; fuzzy control; fuzzy systems; Takagi-Sugeno (T-S); time delay

资金

  1. Key-Area Research and Development Program of Guangdong Province [2020B0909020001]
  2. National Natural Science Foundation of China [62103066, 62106027]
  3. China Postdoctoral Science Foundation [2021TQ0392, 2021M700592]
  4. Chongqing Postdoctoral Innovative Talents Support Program [CQBX2021005]
  5. Chongqing Postdoctoral Science Foundation [cstc2021jcyj-bshX0178, cstc2020jcyj-bsh0060]
  6. Key-Area Research and Development Program of Guangdong Province [2020B0909020001]
  7. National Natural Science Foundation of China [62103066, 62106027]
  8. China Postdoctoral Science Foundation [2021TQ0392, 2021M700592]
  9. Chongqing Postdoctoral Innovative Talents Support Program [CQBX2021005]
  10. Chongqing Postdoctoral Science Foundation [cstc2021jcyj-bshX0178, cstc2020jcyj-bsh0060]

向作者/读者索取更多资源

This article investigates the problem of finite-time control for multiple time-delayed large-scale nonlinear systems, using the Takagi-Sugeno fuzzy model. It designs a dynamic output feedback controller and provides sufficient conditions for finite-time control using fuzzy Lyapunov function. The feasibility of the approach is verified through simulation examples.
In this article, finite-time control is investigated for multiple time-delayed large-scale nonlinear systems against state and input constraints. There are multiple time-varying delays, intermittent actuator faults, and intermittent sensor faults in this model. Takagi-Sugeno fuzzy model is used to describe the nonlinear system. There are few tries to studying finite-time control for large-scale nonlinear systems. First, a dynamic output feedback controller is designed in this article to make the system finite-time bounded. Then, an augmented closed-loop model is constructed. Sufficient conditions of finite-time control are given by the fuzzy Lyapunov function. Finally, the feasibility of the approach is verified by two simulation examples.

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