H∞ fuzzy filter for nonlinear sampled-data system using fuzzy Lyapunov function

Ho Jun Kim; Jin Bae Park; Young Hoon Joo

doi:10.1109/ICCAS.2016.7832505

H_∞ fuzzy filter for nonlinear sampled-data system using fuzzy Lyapunov function

Ho Jun Kim, Jin Bae Park, Young Hoon Joo

Department of Electrical and Electronic Engineering

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

Abstract

This paper proposes an H_∞ fuzzy filter for nonlinear sampled-data system. The nonlinear system is represented based on the Takagi-Sugeno (T-S) fuzzy model. An error system between the nonlinear sampled-data system and fuzzy filter is presented. Using a fuzzy Lyapunov function, sufficient conditions for showing H_∞ performance of the fuzzy filter are proposed. The sufficient conditions are derived in terms of linear matrix inequalities (LMIs) which can be easily solved using convex optimization technique. Finally, simulation example is provided to show the feasiblity of the proposed method.

Original language	English
Title of host publication	ICCAS 2016 - 2016 16th International Conference on Control, Automation and Systems, Proceedings
Publisher	IEEE Computer Society
Pages	1393-1396
Number of pages	4
ISBN (Electronic)	9788993215120
DOIs	https://doi.org/10.1109/ICCAS.2016.7832505
Publication status	Published - 2016 Jan 24
Event	16th International Conference on Control, Automation and Systems, ICCAS 2016 - Gyeongju, Korea, Republic of Duration: 2016 Oct 16 → 2016 Oct 19

Publication series

Name	International Conference on Control, Automation and Systems
Volume	0
ISSN (Print)	1598-7833

Other

Other	16th International Conference on Control, Automation and Systems, ICCAS 2016
Country	Korea, Republic of
City	Gyeongju
Period	16/10/16 → 16/10/19

Bibliographical note

Publisher Copyright:
© 2016 Institute of Control, Robotics and Systems - ICROS.

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Computer Science Applications
Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/ICCAS.2016.7832505

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Kim, H. J., Park, J. B., & Joo, Y. H. (2016). H_∞ fuzzy filter for nonlinear sampled-data system using fuzzy Lyapunov function. In ICCAS 2016 - 2016 16th International Conference on Control, Automation and Systems, Proceedings (pp. 1393-1396). [7832505] (International Conference on Control, Automation and Systems; Vol. 0). IEEE Computer Society. https://doi.org/10.1109/ICCAS.2016.7832505

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abstract = "This paper proposes an H∞ fuzzy filter for nonlinear sampled-data system. The nonlinear system is represented based on the Takagi-Sugeno (T-S) fuzzy model. An error system between the nonlinear sampled-data system and fuzzy filter is presented. Using a fuzzy Lyapunov function, sufficient conditions for showing H∞ performance of the fuzzy filter are proposed. The sufficient conditions are derived in terms of linear matrix inequalities (LMIs) which can be easily solved using convex optimization technique. Finally, simulation example is provided to show the feasiblity of the proposed method.",

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Kim, HJ, Park, JB & Joo, YH 2016, H_∞ fuzzy filter for nonlinear sampled-data system using fuzzy Lyapunov function. in ICCAS 2016 - 2016 16th International Conference on Control, Automation and Systems, Proceedings., 7832505, International Conference on Control, Automation and Systems, vol. 0, IEEE Computer Society, pp. 1393-1396, 16th International Conference on Control, Automation and Systems, ICCAS 2016, Gyeongju, Korea, Republic of, 16/10/16. https://doi.org/10.1109/ICCAS.2016.7832505

H_∞ fuzzy filter for nonlinear sampled-data system using fuzzy Lyapunov function. / Kim, Ho Jun; Park, Jin Bae; Joo, Young Hoon.

ICCAS 2016 - 2016 16th International Conference on Control, Automation and Systems, Proceedings. IEEE Computer Society, 2016. p. 1393-1396 7832505 (International Conference on Control, Automation and Systems; Vol. 0).

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

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AB - This paper proposes an H∞ fuzzy filter for nonlinear sampled-data system. The nonlinear system is represented based on the Takagi-Sugeno (T-S) fuzzy model. An error system between the nonlinear sampled-data system and fuzzy filter is presented. Using a fuzzy Lyapunov function, sufficient conditions for showing H∞ performance of the fuzzy filter are proposed. The sufficient conditions are derived in terms of linear matrix inequalities (LMIs) which can be easily solved using convex optimization technique. Finally, simulation example is provided to show the feasiblity of the proposed method.

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