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.

Iterative linear matrix inequality algorithms for fault detection with unknown inputs

2005 ◽  
Vol 219 (2) ◽  
pp. 161-172 ◽  
Author(s):  
H Wang ◽  
J Lam ◽  
S X Ding ◽  
M Zhong
Keyword(s):  
Fault Detection ◽  
Linear Matrix Inequality ◽  
Linear Time ◽  
Linear Matrix ◽  
Matrix Inequality ◽  
Unknown Inputs ◽  
Linear Time Invariant ◽  
Unknown Disturbances ◽  
Linear Time Invariant Systems ◽  
Iterative Linear Matrix Inequality

This paper deals with the fault detection problem for linear time-invariant systems with unknown disturbances. Two separate performance indices are presented to facilitate the design of desirable fault detection observers. Iterative linear matrix inequality (LMI) algorithms are proposed in order to design a fault detection observer that aims at enhancing the fault detection and attenuating the effects due to unknown inputs. Numerical examples are employed to demonstrate the effectiveness of the proposed methods.

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.

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.

scholarly journals A Survey on Model-Based Fault Detection Techniques for Linear Time-Invariant Systems with Numerical Analysis

2021 ◽  
Vol 30 (1) ◽  
pp. 53-78
Author(s):  
Masood Ahmad ◽  
Rosmiwati Mohd-Mokhta
Keyword(s):  
Fault Detection ◽  
Linear Time ◽  
Fault Detection And Isolation ◽  
Estimation Methods ◽  
Future Research ◽  
Practical Applications ◽  
Detection Techniques ◽  
Linear Time Invariant ◽  
Model Based ◽  
Time Invariant

With the ongoing increase in complexity, less tolerance to performance degradation and safety requirements of practical systems has increased the necessity of fault detection (FD) as early as possible. During the last few decades, many research findings have been developed in fault diagnosis that addresses the issue of fault detection and isolation in linear and nonlinear systems. The paper’s objective is to present a survey on various state-of-art model-based FD techniques developed for linear time-invariant (LTI) systems for the interested readers to learn about recent development in this field. Model-based FD techniques for LTI systems are classified as parameter-estimation methods, parity-space-based methods, and observer-based methods. The background and recent progress, in context to fault detection, of each of these methods and their practical applications are discussed in this paper. Furthermore, two different FD techniques are compared via analytical equations and simulation results obtained from the DC motor model. In the end, possible future research directions in model-based FD, particularly for the LTI system, are highlighted for prosperous researchers. A comparison and emerging research topic make this contribution different from the existing survey papers on FD.

scholarly journals Robust Quasi–LPV Model Reference FTC of a Quadrotor Uav Subject to Actuator Faults

2015 ◽  
Vol 25 (1) ◽  
pp. 7-22 ◽  
Author(s):  
Damiano Rotondo ◽  
Fatiha Nejjari ◽  
Vicenç Puig
Keyword(s):  
Reference Model ◽  
Fault Tolerant ◽  
Linear Time ◽  
Design Procedure ◽  
Pole Placement ◽  
Fault Estimation ◽  
Linear Matrix ◽  
Reference Trajectory ◽  
Model Reference ◽  
Error Models

Abstract A solution for fault tolerant control (FTC) of a quadrotor unmanned aerial vehicle (UAV) is proposed. It relies on model reference-based control, where a reference model generates the desired trajectory. Depending on the type of reference model used for generating the reference trajectory, and on the assumptions about the availability and uncertainty of fault estimation, different error models are obtained. These error models are suitable for passive FTC, active FTC and hybrid FTC, the latter being able to merge the benefits of active and passive FTC while reducing their respective drawbacks. The controller is generated using results from the robust linear parameter varying (LPV) polytopic framework, where the vector of varying parameters is used to schedule between uncertain linear time invariant (LTI) systems. The design procedure relies on solving a set of linear matrix inequalities (LMIs) in order to achieve regional pole placement and H∞ norm bounding constraints. Simulation results are used to compare the different FTC strategies.

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