Distributed Fault Detection and Isolation of Continuous-Time Non-Linear Systems

Boem, Francesca; Ferrari, Riccardo; Parisini, Thomas

doi:10.3166/ejc.17.603-620

Cited by 56 publications

(63 citation statements)

References 114 publications

(148 reference statements)

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“…Due to space constraints the proof of the theorem is omitted, but the steps are similar to those presented in the fault detectability theorem in Boem et al (2011a). Theorem 1.…”

Section: Fault Detectability Analysismentioning

confidence: 99%

“…where H I = ∂ĝ I /∂θ I and PΘ I is a projection operator restrictingθ I withinΘ I (Polycarpou (1998)), Γ I is a symmetric and positive definite learning rate matrix (see for details Boem et al (2011a)). In the general form, the component-wise output estimation error can be bounded by the following threshold, that can be computed in a distributed way:…”

Section: Distributed Detection Architecturementioning

confidence: 99%

“…However, as far as distributed discrete-time or continuous-time systems are concerned, qualitative fault diagnosis schemes were attempted only recently (see as example Lechevin and Rabbath (2009)), or quantitative methods that were formulated for linear systems only (like Stankovič et al (2010)), with Zhang (2010) being one of the few contributions on decentralized fault detection for large-scale nonlinear systems. In this paper, we propose a fault detection and isolation scheme for a class of nonlinear uncertain continuous-time systems, where, furthermore, the system states are only partially measurable (in the recent paper Boem et al (2011a), the full-state case has been dealt with). Though several papers dealing with centralized fault diagnosis schemes for input-output systems have appeared in the literature (Zhang et al (1998(Zhang et al ( , 2001); Subbarao and Vemuri (2007); Zhang and Jaimoukha (2009)), to the best of the authors knowledge this is the first contribution addressing distributed schemes for input-output continuous-time nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Distributed Fault Diagnosis for Input-Output Continuous-Time Nonlinear Systems

Boem

Ferrari

Parisini

et al. 2012

IFAC Proceedings Volumes

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In this paper, new results on distributed fault diagnosis of continuous-time nonlinear systems with partial state measurements are proposed. Following an overlapping decomposition framework, the dynamics of a nonlinear uncertain large-scale dynamical systems is described as the interconnection of several subsystems. Each subsystem is monitored by its own Local Fault Diagnoser, based on a set of local estimators. A consensus-based protocol is used to improve the detectability and the isolability of faults affecting variables shared among different subsystems because of the overlapping decomposition. A sufficient condition assuring the convergence of the estimation errors is derived. Time-varying threshold functions guaranteeing no false-positive alarms and theoretical results containing detectability and isolability conditions are presented.

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“…Due to space constraints the proof of the theorem is omitted, but the steps are similar to those presented in the fault detectability theorem in Boem et al (2011a). Theorem 1.…”

Section: Fault Detectability Analysismentioning

confidence: 99%

Section: Distributed Detection Architecturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Distributed Fault Diagnosis for Input-Output Continuous-Time Nonlinear Systems

Boem

Ferrari

Parisini

et al. 2012

IFAC Proceedings Volumes

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“…On the other hand, the works proposing distributed monitoring schemes for discretetime or continuous-time systems, like Boem et al (2011);Ferrari et al (2012); Zhang and Zhang (2012), assume that the decomposition of the system into subsystems is given a priori. The aim of this work is to study the decomposition problem specifically for the fault detection task.…”

Section: Introductionmentioning

confidence: 99%

“…Recently there has been a growing interest towards distributed architectures for fault diagnosis of large-scale and networked systems (see, for instance Boem et al (2011);Ferrari et al (2012); Zhang and Zhang (2012); Boem et al (2013a,b); Keliris et al (2015); Reppa et al (2015)). As it is well known, the drawbacks of a centralized fault diagnosis architecture are scalability and robustness.…”

Section: Introductionmentioning

confidence: 99%

Optimal Topology for Distributed Fault Detection of Large-scale Systems ★ ★This paper has been partially supported by the EPSRC STABLENET grant EP/L014343/1.

et al. 2015

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The paper deals with the problem of defining the optimal topology for a distributed fault detection architecture for non-linear large-scale systems. A stochastic modelbased framework for diagnosis is formulated. The system structural graph is decomposed into subsystems and each subsystem is monitored by one local diagnoser. It is shown that overlapping of subsystems allows to improve the detectability properties of the monitoring architecture. Based on this theoretical result, an optimal decomposition design method is proposed, able to define the minimum number of detection units needed to guarantee the detectability of certain faults while minimizing the communication costs subject to some computation cost constraints. An algorithmic procedure is presented to solve the proposed optimal decomposition problem. Preliminary simulation results show the potential of the proposed approach.

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Fault Diagnosis for Uncertain Networked Systems

Boem

Keliris

Parisini

et al. 2018

Systems &Amp; Control: Foundations &Amp; Applications

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Fault diagnosis has been at the forefront of technological developments for several decades. Recent advances in many engineering fields have led to the networked interconnection of various systems. The increased complexity of modern systems leads to a larger number of sources of uncertainty which must be taken into consideration and addressed properly in the design of monitoring and fault diagnosis architectures. This chapter reviews a model-based distributed fault diagnosis approach for uncertain nonlinear large-scale networked systems to specifically address: a) the presence of measurement noise by devising a filtering scheme for dampening the effect of noise; b) the modeling of uncertainty by developing an adaptive learning scheme; c) the uncertainty issues emerging when considering networked systems, such as the presence of delays and packet dropouts in the communication networks. The proposed architecture considers in an integrated way the various components of complex distributed systems, such as: the physical environment, the sensor level, the fault diagnosers and the communication networks. Finally, some actions taken after the detection of a fault, such as the identification of the fault location and its magnitude or the learning of the fault function, are illustrated.

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Distributed Fault Detection and Isolation of Continuous-Time Non-Linear Systems

Cited by 56 publications

References 114 publications

Distributed Fault Diagnosis for Input-Output Continuous-Time Nonlinear Systems

Distributed Fault Diagnosis for Input-Output Continuous-Time Nonlinear Systems

Optimal Topology for Distributed Fault Detection of Large-scale Systems ★ ★This paper has been partially supported by the EPSRC STABLENET grant EP/L014343/1.

Fault Diagnosis for Uncertain Networked Systems

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