Dissipative filter design for Takagi-Sugeno fuzzy neural networks

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

doi:10.1109/ICCAS.2015.7364903

Dissipative filter design for Takagi-Sugeno fuzzy neural networks

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

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

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 language	English
Title of host publication	ICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	181-185
Number of pages	5
ISBN (Print)	9788993215090
DOIs	https://doi.org/10.1109/ICCAS.2015.7364903
Publication status	Published - 2015 Dec 23
Event	15th International Conference on Control, Automation and Systems, ICCAS 2015 - Busan, Korea, Republic of Duration: 2015 Oct 13 → 2015 Oct 16

Other

Other	15th International Conference on Control, Automation and Systems, ICCAS 2015
Country/Territory	Korea, Republic of
City	Busan
Period	15/10/13 → 15/10/16

Keywords

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

ASJC Scopus subject areas

Control and Systems Engineering

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10.1109/ICCAS.2015.7364903

Cite this

Dissipative filter design for Takagi-Sugeno fuzzy neural networks. / Lee, Kyu Chul; Choi, Hyun Duk; Kim, Dae Ki et al.
ICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2015. p. 181-185 7364903.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Lee, KC, Choi, HD, Kim, DK, Ahn, CK & Lim, MT 2015, Dissipative filter design for Takagi-Sugeno fuzzy neural networks. in ICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings., 7364903, Institute of Electrical and Electronics Engineers Inc., pp. 181-185, 15th International Conference on Control, Automation and Systems, ICCAS 2015, Busan, Korea, Republic of, 15/10/13. https://doi.org/10.1109/ICCAS.2015.7364903

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title = "Dissipative filter design for Takagi-Sugeno fuzzy neural networks",

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.",

keywords = "Dissipative filtering, Linear matrix inequality(LMI), Takagi-Sugeno fuzzy Hopfield neural network",

author = "Lee, {Kyu Chul} and Choi, {Hyun Duk} and Kim, {Dae Ki} and Ahn, {Choon Ki} and Lim, {Myo Taeg}",

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AU - Lee, Kyu Chul

AU - Choi, Hyun Duk

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AU - Lim, Myo Taeg

PY - 2015/12/23

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AB - 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.

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KW - Linear matrix inequality(LMI)

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Dissipative filter design for Takagi-Sugeno fuzzy neural networks

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Keywords

ASJC Scopus subject areas

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