Fuzzy filter for nonlinear sampled-data systems: Intelligent digital redesign approach

Ho Jun Kim, Jin Bae Park, Young Hoon Joo

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


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
Issue number2
Publication statusPublished - 2017 Apr 1

Bibliographical note

Publisher Copyright:
© 2017, Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg.

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications


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