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 journalArticle

5 Citations (Scopus)

Abstract

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
Volume11
Issue number5
DOIs
Publication statusPublished - 2017 Mar 17

Fingerprint

Fuzzy filters
Fuzzy Filter
Sampled-data Systems
Imperfect
Nonlinear Systems
Disturbance Attenuation
Takagi-Sugeno Fuzzy Model
Asymptotic stability
Linear matrix inequalities
Asymptotic Stability
Lyapunov
Matrix Inequality
Nonlinear systems
Linear Inequalities
Filtering
Sufficient Conditions
Simulation

All Science Journal Classification (ASJC) codes

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

Cite this

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H∞ fuzzy filter for non-linear sampled-data systems under imperfect premise matching. / Kim, Ho Jun; Park, Jin Bae; Joo, Young Hoon.

In: IET Control Theory and Applications, Vol. 11, No. 5, 17.03.2017, p. 747-755.

Research output: Contribution to journalArticle

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AB - 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.

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