Sampled-data H fuzzy filtering for nonlinear systems with missing measurements

Geun Bum Koo, Jin Bae Park, Young Hoon Joo

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

In this paper, a sampled-data H fuzzy filtering problem is considered for nonlinear systems with missing measurements. The nonlinear sampled-data system and missing measurements are assumed to be represented by a Takagi–Sugeno (T–S) fuzzy system and an independent, identically distributed Bernoulli random process, respectively. Based on the fuzzy system, the H fuzzy filtering problem is formulated to design the sampled-data fuzzy filter. By using the exponential mean-square stability definition, the stability condition with an H performance is guaranteed for the fuzzy system with the sampled-data fuzzy filter, and its sufficient condition is converted into the linear matrix inequality (LMI) format. Finally, an example is provided to verify the effectiveness of the proposed fuzzy filtering technique.

Original languageEnglish
Pages (from-to)82-98
Number of pages17
JournalFuzzy Sets and Systems
Volume316
DOIs
Publication statusPublished - 2017 Jun 1

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Fuzzy systems
Fuzzy filters
Fuzzy Filter
Nonlinear systems
Filtering
Nonlinear Systems
Fuzzy Systems
Sampled-data Systems
Mean-square Stability
Takagi-Sugeno Fuzzy Systems
Random process
Exponential Stability
Linear matrix inequalities
Random processes
Bernoulli
Stability Condition
Identically distributed
Matrix Inequality
Linear Inequalities
Verify

All Science Journal Classification (ASJC) codes

  • Logic
  • Artificial Intelligence

Cite this

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abstract = "In this paper, a sampled-data H∞ fuzzy filtering problem is considered for nonlinear systems with missing measurements. The nonlinear sampled-data system and missing measurements are assumed to be represented by a Takagi–Sugeno (T–S) fuzzy system and an independent, identically distributed Bernoulli random process, respectively. Based on the fuzzy system, the H∞ fuzzy filtering problem is formulated to design the sampled-data fuzzy filter. By using the exponential mean-square stability definition, the stability condition with an H∞ performance is guaranteed for the fuzzy system with the sampled-data fuzzy filter, and its sufficient condition is converted into the linear matrix inequality (LMI) format. Finally, an example is provided to verify the effectiveness of the proposed fuzzy filtering technique.",
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Sampled-data H fuzzy filtering for nonlinear systems with missing measurements. / Koo, Geun Bum; Park, Jin Bae; Joo, Young Hoon.

In: Fuzzy Sets and Systems, Vol. 316, 01.06.2017, p. 82-98.

Research output: Contribution to journalArticle

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