Intelligent digital redesign for T–S fuzzy systems: Sampled-data filter approach

Ho Jun Kim, Jin Bae Park, Young Hoon Joo

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


This study proposes an intelligent digital redesign (IDR) technique for sampled-data fuzzy filters of non-linear systems. The technique constructs a closed-loop system with predesigned continuous-time and sampled-data filters based on the Takagi–Sugeno (T–S) fuzzy model. The closed-loop systems ensure asymptotic stability and state-matching condition in the IDR problem. Unlike previous techniques, the proposed method solves the IDR problem without a discretization process which degrades the IDR performance. Sufficient conditions for solving the IDR problem are proposed and derived in terms of linear matrix inequalities. In addition, the performance recovery of the sampled-data fuzzy filter is shown. Finally, the feasibility of the proposed technique is demonstrated in two simulation examples.

Original languageEnglish
Pages (from-to)1306-1317
Number of pages12
JournalIET Control Theory and Applications
Issue number9
Publication statusPublished - 2018 Jun 12

Bibliographical note

Funding Information:
This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF 2016R1A6A1A03013567) and by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry & Energy (MOTIE) of the Republic of Korea (no. 20174030201670).

Publisher Copyright:
© The Institution of Engineering and Technology 2018.

All Science Journal Classification (ASJC) codes

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


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