A Fault Prediction Scheme for Takagi-Sugeno Fuzzy Systems with Immeasurable Premise Variables and Disturbance

被引：0

作者：

Thumati, Balaje T. ^{[1
]}

Sarangapani, Jagannathan ^{[2
]}

机构：

[1] Boeing Co, Seattle, WA 98108 USA

[2] Missouri S&T, Dept Elect & Comp Engn, Rolla, MO 65409 USA

来源：

2014 IEEE 53RD ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC) | 2014年

关键词：

Fuzzy systems; immeasurable premise variables; fault detection; prognostics; OBSERVER DESIGN;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

As explained in the literature, it is very hard to measure premise variables of a Takagi-Sugeno (TS) fuzzy system. Therefore, in this paper, a fault detection and prediction (FDP) scheme is designed for a class of TS fuzzy systems with immeasurable (unknown) premise variables and external disturbances. A fault detection (FD) observer is designed to approximate the system output and the premise variables. Subsequently, a FD residual is generated by comparing the observer output with respect to the system output. The FD residual is evaluated to detect any faults in the system. Further, time-to-failure (TTF) of the TS fuzzy system is obtained by using a mathematical equation. Note the parameter update law and TTF scheme utilize the approximated premise variables since they are not measurable. Stability of the fault detection and TTF prediction results are verified using Lyapunov theory. Finally, a simulation study using a truck-trailer system is presented to verify the theoretical claims.

引用

页码：6758 / 6763

页数：6

共 19 条

[1]

Aouaouda S., 2012, INT J ADAPTIVE CONTR

[2]

Bergsten P., 2000, P IEEE INT FUZZ SYST, P1498

[3]

Castillo-Toledo B, 2005, 2005 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL & 13TH MEDITERRANEAN CONFERENCE ON CONTROL AND AUTOMATION, VOLS 1 AND 2, P652

[4] RETRACTED: Robust Observer Design for Unknown Inputs Takagi-Sugeno Models (Retracted Article) [J].

Chadli, Mohammed ;

Karimi, Hamid Reza .

IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2013, 21 (01) :158-164

[5]

Chen W, 2007, P AMER CONTR CONF, P245

[6] An approach for the state estimation of Takagi-Sugeno models and application to sensor fault diagnosis [J].

Ichalal, Datil ;

Marx, Benoit ;

Ragot, Jose ;

Maquin, Didier .

PROCEEDINGS OF THE 48TH IEEE CONFERENCE ON DECISION AND CONTROL, 2009 HELD JOINTLY WITH THE 2009 28TH CHINESE CONTROL CONFERENCE (CDC/CCC 2009), 2009, :7789-7794

[7]

Isermann R., 2005, Fault-diagnosis systems: an introduction from fault detection to fault tolerance

[8]

Jagannathan S., 2006, Neural Network Control of Nonlinear Discrete-Time Systems

[9] Adaptive observer for fault estimation in nonlinear systems described by a Takagi-Sugeno model [J].

Khedher, Atef ;

Benothman, Kamel ;

Benrejeb, Mohamed ;

Maquin, Didier .

18TH MEDITERRANEAN CONFERENCE ON CONTROL AND AUTOMATION, 2010, :261-266

[10]

Luo JH, 2003, IEEE SYS MAN CYBERN, P189

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