Fuzzy filter for nonlinear sampled-data systems

Intelligent digital redesign approach

Ho Jun Kim, Jin Bae Park, Young Hoon Joo

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper presents a fuzzy filter design method for nonlinear sampled-data systems using an intelligent digital redesign (IDR) technique. Based on a Takagi–Sugeno (T–S) fuzzy model, discretized closed-loop systems with pre-designed analog fuzzy and digital fuzzy filters are presented. An IDR problem is given to guarantee both state-matching condition and asymptotic stability. Sufficient conditions for solving the IDR problem are proposed and are derived in terms of linear matrix inequalities (LMIs). Finally, a simulation example is given to show the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)603-610
Number of pages8
JournalInternational Journal of Control, Automation and Systems
Volume15
Issue number2
DOIs
Publication statusPublished - 2017 Apr 1

Fingerprint

Fuzzy filters
Intelligent systems
Asymptotic stability
Linear matrix inequalities
Closed loop systems

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications

Cite this

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Fuzzy filter for nonlinear sampled-data systems : Intelligent digital redesign approach. / Kim, Ho Jun; Park, Jin Bae; Joo, Young Hoon.

In: International Journal of Control, Automation and Systems, Vol. 15, No. 2, 01.04.2017, p. 603-610.

Research output: Contribution to journalArticle

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