An improved H fuzzy filter for nonlinear sampled-data systems

Ho Jun Kim, Jin Bae Park, Young Hoon Joo

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


This paper presents an H fuzzy filter design method for nonlinear sampled-data systems that are represented by a Takagi–Sugeno (T–S) fuzzy model. An error system between the T–S fuzzy system and the fuzzy filter is obtained to analyze the sampled-data system and solve the filter synthesis problem. To enhance the feasibility of the sampled-data fuzzy filter, an improved approach is proposed that not only captures the characteristics of the sampled-data system, but also eliminates a complex discretized model of the sampled-data system using a Lyapunov function and two null terms. In the sense of Lyapunov, relaxed sufficient conditions, which are derived in terms of linear matrix inequalities (LMIs), are obtained for both asymptotic stability and H disturbance attenuation performance of the error system with less conservatism. Finally, simulation examples are presented to show the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)1394-1404
Number of pages11
JournalInternational Journal of Control, Automation and Systems
Issue number3
Publication statusPublished - 2017 Jun 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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