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

Sun Young Noh; Jin Bae Park; Young Hoon Joo

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

Sun Young Noh, Jin Bae Park, Young Hoon Joo

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	ICCAS 2010 - International Conference on Control, Automation and Systems
Pages	663-667
Number of pages	5
Publication status	Published - 2010 Dec 1
Event	International Conference on Control, Automation and Systems, ICCAS 2010 - Gyeonggi-do, Korea, Republic of Duration: 2010 Oct 27 → 2010 Oct 30

Other

Other	International Conference on Control, Automation and Systems, ICCAS 2010
Country	Korea, Republic of
City	Gyeonggi-do
Period	10/10/27 → 10/10/30

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Control and Systems Engineering

Access to Document

Fingerprint Dive into the research topics of 'A fuzzy filter with missing measurement for observer-based T-S fuzzy models'. Together they form a unique fingerprint.

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]

@inproceedings{591df3088022487f9eee0574a945742d,

title = "A fuzzy filter with missing measurement for observer-based T-S fuzzy models",

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.",

author = "Noh, {Sun Young} and Park, {Jin Bae} and Joo, {Young Hoon}",

year = "2010",

month = dec,

day = "1",

language = "English",

isbn = "9781424474530",

pages = "663--667",

booktitle = "ICCAS 2010 - International Conference on Control, Automation and Systems",

note = "International Conference on Control, Automation and Systems, ICCAS 2010 ; Conference date: 27-10-2010 Through 30-10-2010",

}

TY - GEN

T1 - A fuzzy filter with missing measurement for observer-based T-S fuzzy models

AU - Noh, Sun Young

AU - Park, Jin Bae

AU - Joo, Young Hoon

PY - 2010/12/1

Y1 - 2010/12/1

N2 - 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.

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.

UR - http://www.scopus.com/inward/record.url?scp=78751559469&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78751559469&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:78751559469

SN - 9781424474530

SP - 663

EP - 667

BT - ICCAS 2010 - International Conference on Control, Automation and Systems

T2 - International Conference on Control, Automation and Systems, ICCAS 2010

Y2 - 27 October 2010 through 30 October 2010

ER -