Fault detection for discrete-time linear systems based on descriptor observer approach

Du, Dongsheng

doi:10.1016/j.amc.2016.08.052

Cited by 25 publications

(5 citation statements)

References 19 publications

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“…Ferdowsi et al designed a fault detection observer using the PDE direct representation of the original system [23]. Similarly, the fault detection method by designing observers in linear DPS systems has been widely used [24] [25] [26]. Dey, Perez and Moura studied the problem of robust fault detection in a linear parabolic system with uncertainties [27].…”

Section: Introductionmentioning

confidence: 99%

Actuator Fault Diagnosis for a Class of One-Dimensional Nonlinear Heat Equations via Backstepping Method

Chen¹

2023

OJAppS

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In this paper, an actuator fault diagnosis scheme based on the backstepping method is proposed for a class of nonlinear heat equations. The fault diagnosis scheme includes fault detection, fault estimation and time to failure (TTF) prediction. Firstly, we achieve fault detection by comparing the detection residual with a predetermined threshold, where the detection residual is defined as the difference between the observer output and the system measurement output. Then, we estimate the fault function through the fault parameter update law and calculate the TTF using only limited measurements. Finally, the numerical simulation is performed on a nonlinear heat equation to verify the effectiveness of the proposed fault diagnosis scheme.

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Section: Introductionmentioning

confidence: 99%

Actuator Fault Diagnosis for a Class of One-Dimensional Nonlinear Heat Equations via Backstepping Method

Chen¹

2023

OJAppS

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“…Ferdowsi and Jagannathan constructed the fault diagnosis observer of DPS by using the direct representation of PDE of the system, and realized the fault diagnosis of DPS of a class of parabolic PDE [9]. At the same time, observer-based fault detection methods have been widely used in linear systems and some important studies have been made in [10] [11] [12]. For example, Cai, Ferdowsi and Sarangapani constructed a new model-based fault detection method in [13], in which a state observer was constructed based on the boundary measurements of the original PDE system.…”

Section: Introductionmentioning

confidence: 99%

Backstepping-Based Distributed Abnormality Detection for Nolinear Parabolic Distributed Prameter Systems

Chen¹

2022

ENG

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In this paper, we proposed a model-based abnormality detection scheme for a class of nonlinear parabolic distributed parameter systems (DPSs). The proposed methodology consists of the design of an observer and an abnormality detection filter (ADF) based on the backstepping technique and a limited number of in-domain measurements plus one boundary measurement. By taking the difference between the measured and estimated outputs from observer, a residual signal is generated for fault detection. For the detection purpose, the residual is evaluated in a lumped manner and we propose an explicit expression for the time-varying threshold. The convergence properties of the PDE observer and the residual are analyzed by Lyapunov stability theory. Eventually, the proposed abnormality detection scheme is demonstrated on a nonlinear DPS.

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“…Various researchers have used observational techniques, based on different algorithms. Examples include the proportional-integral (PI) technique [31,32], proportional multiple-integral (PMI) method [33,34,35], descriptor technique [36,37], adaptive methods [38,39,40], sliding mode techniques [41,42,43,44], and feedback linearization techniques [45,46]. Linear observer methods (e.g., PI and PMI) have been used in various applications for FDD, but these techniques have challenges in the presence of uncertainties [47,48].…”

Section: Introductionmentioning

confidence: 99%

Bearing Fault Diagnosis Using an Extended Variable Structure Feedback Linearization Observer

Piltan

Kim

2018

Sensors

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The rolling element bearing is a significant component in rotating machinery. Suitable bearing fault detection and diagnosis (FDD) is vital to maintaining machine operations in a safe and healthy state. To address this issue, an extended observer-based FDD method is proposed, which uses a variable structure feedback linearization observer (FLO). The traditional feedback linearization observer is stable; however, this technique suffers from a lack of robustness. The proposed variable structure technique was used to improve the robustness of the fault estimation while reducing the uncertainties in the feedback linearization observer. The effectiveness of the proposed FLO procedure for the identification of outer, inner, and ball faults was tested using the Case Western University vibration dataset. The proposed model outperformed the variable structure observer (VSO), traditional feedback linearization observer (TFLO), and proportional-integral observer (PIO) by achieving average performance improvements of 5.5%, 8.5%, and 18.5%, respectively.

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Fault detection for discrete-time linear systems based on descriptor observer approach

Cited by 25 publications

References 19 publications

Actuator Fault Diagnosis for a Class of One-Dimensional Nonlinear Heat Equations via Backstepping Method

Actuator Fault Diagnosis for a Class of One-Dimensional Nonlinear Heat Equations via Backstepping Method

Backstepping-Based Distributed Abnormality Detection for Nolinear Parabolic Distributed Prameter Systems

Bearing Fault Diagnosis Using an Extended Variable Structure Feedback Linearization Observer

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