A fuzzy filter with missing measurement for observer-based T-S fuzzy models

Sun Young Noh, Jin Bae Park, Young Hoon Joo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper is concerned with the problem of a fuzzy filter of nonlinear system with missing measurements. The nonlinear system is represented by a Takagi-Sugeno(TS) fuzzy model. The system measurements may be unavailable at any sample time and the probability of the occurrence of missing data is assumed to be known. The purpose of this problem is to design a linear filter such that, the error state of the filtering process is mean square bounded. A basis-dependent Lyapunov function approach is developed to design the fuzzy filter, and it is developed the upper bound of a fuzzy filter gain of the estimation error subject to some LMI constraints. In this situation, the estimation error due to persistent bounded disturbances. Finally, an illustrative numerical example is provided to show the effectiveness of the proposed approach.

Original languageEnglish
Title of host publicationICCAS 2010 - International Conference on Control, Automation and Systems
Pages663-667
Number of pages5
Publication statusPublished - 2010 Dec 1
EventInternational Conference on Control, Automation and Systems, ICCAS 2010 - Gyeonggi-do, Korea, Republic of
Duration: 2010 Oct 272010 Oct 30

Other

OtherInternational Conference on Control, Automation and Systems, ICCAS 2010
CountryKorea, Republic of
CityGyeonggi-do
Period10/10/2710/10/30

Fingerprint

Fuzzy filters
Error analysis
Nonlinear systems
Lyapunov functions

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Control and Systems Engineering

Cite this

Noh, S. Y., Park, J. B., & Joo, Y. H. (2010). A fuzzy filter with missing measurement for observer-based T-S fuzzy models. In ICCAS 2010 - International Conference on Control, Automation and Systems (pp. 663-667). [5670231]
Noh, Sun Young ; Park, Jin Bae ; Joo, Young Hoon. / A fuzzy filter with missing measurement for observer-based T-S fuzzy models. ICCAS 2010 - International Conference on Control, Automation and Systems. 2010. pp. 663-667
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Noh, SY, Park, JB & Joo, YH 2010, A fuzzy filter with missing measurement for observer-based T-S fuzzy models. in ICCAS 2010 - International Conference on Control, Automation and Systems., 5670231, pp. 663-667, International Conference on Control, Automation and Systems, ICCAS 2010, Gyeonggi-do, Korea, Republic of, 10/10/27.

A fuzzy filter with missing measurement for observer-based T-S fuzzy models. / Noh, Sun Young; Park, Jin Bae; Joo, Young Hoon.

ICCAS 2010 - International Conference on Control, Automation and Systems. 2010. p. 663-667 5670231.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - This paper is concerned with the problem of a fuzzy filter of nonlinear system with missing measurements. The nonlinear system is represented by a Takagi-Sugeno(TS) fuzzy model. The system measurements may be unavailable at any sample time and the probability of the occurrence of missing data is assumed to be known. The purpose of this problem is to design a linear filter such that, the error state of the filtering process is mean square bounded. A basis-dependent Lyapunov function approach is developed to design the fuzzy filter, and it is developed the upper bound of a fuzzy filter gain of the estimation error subject to some LMI constraints. In this situation, the estimation error due to persistent bounded disturbances. Finally, an illustrative numerical example is provided to show the effectiveness of the proposed approach.

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Noh SY, Park JB, Joo YH. A fuzzy filter with missing measurement for observer-based T-S fuzzy models. In ICCAS 2010 - International Conference on Control, Automation and Systems. 2010. p. 663-667. 5670231