Intelligent digital redesign for T–S fuzzy systems: Sampled-data filter approach

Ho Jun Kim, Jin Bae Park, Young Hoon Joo

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This study proposes an intelligent digital redesign (IDR) technique for sampled-data fuzzy filters of non-linear systems. The technique constructs a closed-loop system with predesigned continuous-time and sampled-data filters based on the Takagi–Sugeno (T–S) fuzzy model. The closed-loop systems ensure asymptotic stability and state-matching condition in the IDR problem. Unlike previous techniques, the proposed method solves the IDR problem without a discretization process which degrades the IDR performance. Sufficient conditions for solving the IDR problem are proposed and derived in terms of linear matrix inequalities. In addition, the performance recovery of the sampled-data fuzzy filter is shown. Finally, the feasibility of the proposed technique is demonstrated in two simulation examples.

Original languageEnglish
Pages (from-to)1306-1317
Number of pages12
JournalIET Control Theory and Applications
Volume12
Issue number9
DOIs
Publication statusPublished - 2018 Jun 12

Fingerprint

Fuzzy filters
Digital Redesign
Takagi-Sugeno Fuzzy Systems
Fuzzy systems
Closed loop systems
Filter
Fuzzy Filter
Asymptotic stability
Linear matrix inequalities
System stability
Nonlinear systems
Closed-loop System
Recovery
Takagi-Sugeno Fuzzy Model
Asymptotic Stability
Matrix Inequality
Continuous Time
Linear Inequalities
Nonlinear Systems
Discretization

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Control and Optimization
  • Electrical and Electronic Engineering

Cite this

@article{4e5ad1f31ec44d7c893e20ca31992be8,
title = "Intelligent digital redesign for T–S fuzzy systems: Sampled-data filter approach",
abstract = "This study proposes an intelligent digital redesign (IDR) technique for sampled-data fuzzy filters of non-linear systems. The technique constructs a closed-loop system with predesigned continuous-time and sampled-data filters based on the Takagi–Sugeno (T–S) fuzzy model. The closed-loop systems ensure asymptotic stability and state-matching condition in the IDR problem. Unlike previous techniques, the proposed method solves the IDR problem without a discretization process which degrades the IDR performance. Sufficient conditions for solving the IDR problem are proposed and derived in terms of linear matrix inequalities. In addition, the performance recovery of the sampled-data fuzzy filter is shown. Finally, the feasibility of the proposed technique is demonstrated in two simulation examples.",
author = "Kim, {Ho Jun} and Park, {Jin Bae} and Joo, {Young Hoon}",
year = "2018",
month = "6",
day = "12",
doi = "10.1049/iet-cta.2017.0964",
language = "English",
volume = "12",
pages = "1306--1317",
journal = "IET Control Theory and Applications",
issn = "1751-8644",
publisher = "Institution of Engineering and Technology",
number = "9",

}

Intelligent digital redesign for T–S fuzzy systems : Sampled-data filter approach. / Kim, Ho Jun; Park, Jin Bae; Joo, Young Hoon.

In: IET Control Theory and Applications, Vol. 12, No. 9, 12.06.2018, p. 1306-1317.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Intelligent digital redesign for T–S fuzzy systems

T2 - Sampled-data filter approach

AU - Kim, Ho Jun

AU - Park, Jin Bae

AU - Joo, Young Hoon

PY - 2018/6/12

Y1 - 2018/6/12

N2 - This study proposes an intelligent digital redesign (IDR) technique for sampled-data fuzzy filters of non-linear systems. The technique constructs a closed-loop system with predesigned continuous-time and sampled-data filters based on the Takagi–Sugeno (T–S) fuzzy model. The closed-loop systems ensure asymptotic stability and state-matching condition in the IDR problem. Unlike previous techniques, the proposed method solves the IDR problem without a discretization process which degrades the IDR performance. Sufficient conditions for solving the IDR problem are proposed and derived in terms of linear matrix inequalities. In addition, the performance recovery of the sampled-data fuzzy filter is shown. Finally, the feasibility of the proposed technique is demonstrated in two simulation examples.

AB - This study proposes an intelligent digital redesign (IDR) technique for sampled-data fuzzy filters of non-linear systems. The technique constructs a closed-loop system with predesigned continuous-time and sampled-data filters based on the Takagi–Sugeno (T–S) fuzzy model. The closed-loop systems ensure asymptotic stability and state-matching condition in the IDR problem. Unlike previous techniques, the proposed method solves the IDR problem without a discretization process which degrades the IDR performance. Sufficient conditions for solving the IDR problem are proposed and derived in terms of linear matrix inequalities. In addition, the performance recovery of the sampled-data fuzzy filter is shown. Finally, the feasibility of the proposed technique is demonstrated in two simulation examples.

UR - http://www.scopus.com/inward/record.url?scp=85047727659&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85047727659&partnerID=8YFLogxK

U2 - 10.1049/iet-cta.2017.0964

DO - 10.1049/iet-cta.2017.0964

M3 - Article

AN - SCOPUS:85047727659

VL - 12

SP - 1306

EP - 1317

JO - IET Control Theory and Applications

JF - IET Control Theory and Applications

SN - 1751-8644

IS - 9

ER -