An improved H ∞ fuzzy filter for nonlinear sampled-data systems

Ho Jun Kim; Jin Bae Park; Young Hoon Joo

doi:10.1007/s12555-016-0088-5

An improved H _∞ fuzzy filter for nonlinear sampled-data systems

Ho Jun Kim, Jin Bae Park, Young Hoon Joo

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

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 language	English
Pages (from-to)	1394-1404
Number of pages	11
Journal	International Journal of Control, Automation and Systems
Volume	15
Issue number	3
DOIs	https://doi.org/10.1007/s12555-016-0088-5
Publication status	Published - 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

Access to Document

10.1007/s12555-016-0088-5

Cite this

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