Dissipative filter design for Takagi-Sugeno fuzzy neural networks

Kyu Chul Lee, Hyun Duk Choi, Dae Ki Kim, Choon Ki Ahn, Myo Taeg Lim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper proposes a novel dissipative filter for Takagi-Sugeno fuzzy Hopfield neural networks with time varying delay. This filter guarantees (Q, S, R)-a-dissipativity and is regarded as a generalization of some performance indices, such as H performance, passivity, and mixed H/passivity. The linear matrix inequality (LMI) approach solving convex problem is used to obtain a gain matrix satisfying both (Q, S, R)-a-dissipativity and asymptotic stability of the error system. Some simulations are dealt with to validate the performance of the proposed method.

Original languageEnglish
Title of host publicationICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages181-185
Number of pages5
ISBN (Electronic)9788993215090
DOIs
StatePublished - 23 Dec 2015
Event15th International Conference on Control, Automation and Systems, ICCAS 2015 - Busan, Korea, Republic of
Duration: 13 Oct 201516 Oct 2015

Publication series

NameICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings

Conference

Conference15th International Conference on Control, Automation and Systems, ICCAS 2015
Country/TerritoryKorea, Republic of
CityBusan
Period13/10/1516/10/15

Keywords

  • Dissipative filtering
  • Linear matrix inequality(LMI)
  • Takagi-Sugeno fuzzy Hopfield neural network

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