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Event-Triggered-Based Adaptive Sliding Mode Control for T-S Fuzzy Systems with Actuator Failures and Signal Quantization

  • Min Li*
  • , Peng Shi
  • , Ming Liu
  • , Yingchun Zhang
  • , Shuoyu Wang
  • *Corresponding author for this work
  • School of Astronautics, Harbin Institute of Technology
  • Adelaide University
  • Victoria University
  • Shenzhen Aerospace Dongfanghong Satellite
  • Kochi University of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

This article investigates the problem of event-triggered-based sliding mode control (SMC) for a class of Takagi-Sugeno (T-S) fuzzy systems with actuator failures and signal quantization. The classical dynamic uniform quantization strategy is employed to quantize data in both sensor-controller side and controller-actuator side. A new event-triggered adaptive SMC scheme is proposed to stabilize the fault closed-loop systems, where the event-triggered condition is based on quantized state vectors. Reachability of the proposed sliding surface can be ensured by the designed control scheme. Furthermore, the existence of minimal inter-event time and sufficient conditions under which zeno behavior can be avoided is analyzed and presented. Finally, two examples are provided to demonstrate the effectiveness of the proposed new design techniques.

Original languageEnglish
Article number9000557
Pages (from-to)1363-1374
Number of pages12
JournalIEEE Transactions on Fuzzy Systems
Volume29
Issue number6
DOIs
StatePublished - Jun 2021
Externally publishedYes

Keywords

  • Event-triggered control (ETC)
  • Takagi-Sugeno (T-S) fuzzy systems
  • signal quantization
  • sliding mode control (SMC)

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