Linear-Matrix-Inequality-Based Robust Fault Detection and Isolation Using the Eigenstructure Assignment Method

2007 ◽  
Vol 30 (6) ◽  
pp. 1831-1835 ◽  
Author(s):  
Bilei Chen ◽  
Satish Nagarajaiah
Keyword(s):  
Fault Detection ◽  
Linear Matrix Inequality ◽  
Fault Detection And Isolation ◽  
Linear Matrix ◽  
Eigenstructure Assignment ◽  
Matrix Inequality ◽  
Assignment Method ◽  
Robust Fault Detection

Linear-Matrix-Inequality-Based Fault Diagnosis for Gas Turbofan Engine Using Eigenstructure Assignment Principle

2013 ◽  
Vol 302 ◽  
pp. 759-764 ◽  
Author(s):  
Yue Liu ◽  
Dao Liang Tan ◽  
Bin Wang ◽  
Xi Wang
Keyword(s):  
Fault Detection ◽  
Linear Matrix Inequality ◽  
Aircraft Engine ◽  
Fault Detection And Isolation ◽  
Linear Matrix ◽  
Eigenstructure Assignment ◽  
Matrix Inequality ◽  
Turbofan Engine ◽  
Suggested Approach ◽  
Assignment Method

This paper proposes an eigenstructure assignment method for engine control system diagnosis based on disturbance decoupling, since noisy disturbance has an adverse impact on the performance of aircraft engine fault detection and isolation (FDI). In practice, it is often difficult to solve the eigenstructure assignment method, and the result is far from being satisfactory. In view of this, the paper makes an attempt to deal with the issue by linear matrix inequality (LMI). The advantages of the presented method are as follows: first, it can reduce the effect of exogenous disturbance on fault detection; In the meantime, it will not impair sensitivity to system faults. Experimental results show that the suggested approach performs well on the simulation of an advanced turbofan engine.

scholarly journals Computation of a Reference Model for Robust Fault Detection and Isolation Residual Generation

2008 ◽  
Vol 2008 ◽  
pp. 1-12 ◽  
Author(s):  
Emmanuel Mazars ◽  
Imad M. Jaimoukha ◽  
Zhenhai Li
Keyword(s):  
Fault Detection ◽  
Reference Model ◽  
Linear Time ◽  
Design Procedure ◽  
Fault Detection And Isolation ◽  
Linear Matrix ◽  
Matrix Inequality ◽  
Lmi Optimization ◽  
Linear Time Invariant ◽  
Robust Fault Detection

This paper considers matrix inequality procedures to address the robust fault detection and isolation (FDI) problem for linear time-invariant systems subject to disturbances, faults, and polytopic or norm-bounded uncertainties. We propose a design procedure for an FDI filter that aims to minimize a weighted combination of the sensitivity of the residual signal to disturbances and modeling errors, and the deviation of the faults to residual dynamics from a fault to residual reference model, using theℋ∞-norm as a measure. A key step in our procedure is the design of an optimal fault reference model. We show that the optimal design requires the solution of a quadratic matrix inequality (QMI) optimization problem. Since the solution of the optimal problem is intractable, we propose a linearization technique to derive a numerically tractable suboptimal design procedure that requires the solution of a linear matrix inequality (LMI) optimization. A jet engine example is employed to demonstrate the effectiveness of the proposed approach.

Robust Unknown Input Observer for Nonlinear Systems and Its Application to Fault Detection and Isolation

2008 ◽  
Vol 130 (4) ◽  
Author(s):  
S. Mondal ◽  
G. Chakraborty ◽  
K. Bhattacharyya
Keyword(s):  
Fault Diagnosis ◽  
Nonlinear System ◽  
Fault Detection ◽  
Nonlinear Function ◽  
Fault Detection And Isolation ◽  
Linear Matrix ◽  
Unknown Input ◽  
Matrix Inequality ◽  
Unknown Input Observer ◽  
Linear Matrix Inequality Approach

A robust unknown input observer for a nonlinear system whose nonlinear function satisfies the Lipschitz condition is designed based on linear matrix inequality approach. Both noise and uncertainties are taken into account in deriving the observer. A component fault detection and isolation scheme based on these observers is proposed. The effectiveness of the observer and the fault diagnosis scheme is shown by applying them for component fault diagnosis of an electrohydraulic actuator.

An LMI Approach to Mixed H_/H∞ Robust Fault Detection Observer Design

2012 ◽  
Vol 546-547 ◽  
pp. 874-879 ◽  
Author(s):  
Ying Chun Zhang ◽  
Li Na Wu ◽  
Zheng Fang Wang ◽  
Qing Xian Jia
Keyword(s):  
Fault Detection ◽  
Uncertain Systems ◽  
Optimization Problems ◽  
Observer Design ◽  
Linear Matrix ◽  
Matrix Inequality ◽  
Matrix Inequalities ◽  
Lmi Approach ◽  
Robust Fault Detection ◽  
Iterative Linear Matrix Inequality

This paper investigates the problem of the robust fault detection (RFD) observer design for linear uncertain systems with the aid of the H_ index and the H∞ norm, which are used to describe the problem of this observer design as optimization problems. Conditions for the existence of such a fault detection observer are given in terms of matrix inequalities. RFD problem with structured uncertainties in the system matrices is also considered. The solution is obtained by an iterative linear matrix inequality (ILMI) algorithm. Numerical example is employed to demonstrate the effectiveness of the proposed methods.

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