Decentralized sampled-data H fuzzy filter for nonlinear large-scale systems

Ho Jun Kim, Geun Bum Koo, Jin Bae Park, Young Hoon Joo

Research output: Contribution to journalArticle

32 Citations (Scopus)

Abstract

This paper presents a decentralized sampled-data H fuzzy filter design method for nonlinear large-scale systems which are represented by a Takagi-Sugeno (T-S) fuzzy model. Based on the T-S fuzzy model, the error system between the nonlinear large-scale system and the filter is obtained. The discretization process of the error system is accomplished with the exact discrete-time approach to eliminate the exact-approximate mismatch. By using the discrete-time Lyapunov sense, the sufficient condition of the asymptotic stability for the error system is given and a prescribed level of the H norm is ensured to guarantee the H fuzzy filter performance. Finally, numerical examples are given to show the effectiveness of the proposed methods.

Original languageEnglish
Pages (from-to)68-86
Number of pages19
JournalFuzzy Sets and Systems
Volume273
DOIs
Publication statusPublished - 2015 Aug 15

All Science Journal Classification (ASJC) codes

  • Logic
  • Artificial Intelligence

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