Event-Triggered Fuzzy Filtering for Nonlinear Dynamic Systems via Reduced-Order Appraoch

Xiaojie Su, Yao Wen, Peng Shi, Hak Keung Lam

Research output: Contribution to journalArticlepeer-review

83 Citations (Scopus)
286 Downloads (Pure)

Abstract

This paper is concerned with the problem of generalized H2 reduced-order filter design for continuous Takagi-Sugeno fuzzy systems using an event-triggered scheme. For a continuous Takagi-Sugeno fuzzy dynamic system, we want to establish a reduced-order filter to transform the original model into a linear lower-order one. This filter can also approximate the original system with H2 performance, with a new type of event-triggered scheme used to decrease the communication loads and computation resources within the network. By transforming the filtering problem to a convex optimization one, conditions are presented to design the fuzzy reduced-order filter. Finally, two illustrative examples are used to verify the feasibility and applicability of the proposed design scheme.

Original languageEnglish
JournalIEEE Transactions on Fuzzy Systems
Early online date4 Oct 2018
DOIs
Publication statusE-pub ahead of print - 4 Oct 2018

Keywords

  • Delays
  • Electronic mail
  • Fault detection
  • Fuzzy filter
  • Fuzzy systems
  • H2 filtering
  • Kalman filters
  • Mathematical model
  • Reduced-order approach

Fingerprint

Dive into the research topics of 'Event-Triggered Fuzzy Filtering for Nonlinear Dynamic Systems via Reduced-Order Appraoch'. Together they form a unique fingerprint.

Cite this