H∞ fuzzy filter for non-linear sampled-data systems under imperfect premise matching

Ho Jun Kim, Jin Bae Park, Young Hoon Joo

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


This study proposes an H∞ fuzzy filtering technique for non-linear sampled-data systems that are represented on the basis of the Takagi-Sugeno fuzzy model. To improve the performance of the fuzzy filter, an imperfect premise matching condition is considered. An error system between the non-linear system and the fuzzy filter is constructed. In addition, sufficient conditions for showing asymptotic stability and guaranteeing H∞ disturbance attenuation performance are proposed in a Lyapunov sense and derived in terms of linear matrix inequalities. Finally, the feasibility of the proposed technique is demonstrated using two simulation examples.

Original languageEnglish
Pages (from-to)747-755
Number of pages9
JournalIET Control Theory and Applications
Issue number5
Publication statusPublished - 2017 Mar 17

Bibliographical note

Publisher Copyright:
© The Institution of Engineering and Technology 2016.

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Control and Optimization
  • Electrical and Electronic Engineering


Dive into the research topics of 'H∞ fuzzy filter for non-linear sampled-data systems under imperfect premise matching'. Together they form a unique fingerprint.

Cite this