Distributed diagnosis for qualitative systems

Su, Rong; Wonham, W. M.; Kurien, James; Koutsoukos, Xenofon

doi:10.1109/wodes.2002.1167684

Cited by 58 publications

(46 citation statements)

References 8 publications

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“…Another advance was made in Su et al (2002) where the authors focus on qualitative systems. They propose an automaton-based distributed diagnosis method.…”

Section: Modular Fault Diagnosis Based On Discrete Event Systemsmentioning

confidence: 99%

Modular Fault Diagnosis Based on Discrete Event Systems

García

Correcher

Morant

et al. 2005

Discrete Event Dyn Syst

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An awareness of failure type and location is an indispensable requirement for the establishment of adequate recovery strategies and the maintenance of Factory Automation and Process Control systems.The failure diagnosis methodology presented in this paper is based on Discrete Event Systems models and in the diagnoser concept, which enable the off-line and on-line analysis of systems failures. We present an approach for models and associated diagnosers based on a modular decomposition of the global system, with the aim of avoiding problems of exponential explosion in the number of states and computational complexity of the diagnosis process.

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“…Another advance was made in Su et al (2002) where the authors focus on qualitative systems. They propose an automaton-based distributed diagnosis method.…”

Section: Modular Fault Diagnosis Based On Discrete Event Systemsmentioning

confidence: 99%

Modular Fault Diagnosis Based on Discrete Event Systems

García

Correcher

Morant

et al. 2005

Discrete Event Dyn Syst

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show abstract

“…The same consideration motivates our choice of Petri net structures as a means to mitigate the combinatorial explosion that occurs when modular models are converted to monolithic ones. Our approach is different from that in related work such as [4], [8], [13], [14] and thus our work is complementary to these references.…”

Section: Introductionmentioning

confidence: 96%

“…Systems possessing modular structures are receiving more and more attention in the recent literature on diagnosis, verification, and control of discrete-event systems; see, e.g., [4], [8], [9], [12], [13]. The suitability of Petri nets to model distributed systems was a key motivation for the use of Petri net structures in the work in [8] on alarm supervision in telecommunication networks.…”

Section: Introductionmentioning

confidence: 99%

Distributed Diagnosis of Place-Bordered Petri Nets

Genç

Lafortune

2007

IEEE Trans. Automat. Sci. Eng.

120

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Abstract-This paper studies on-line fault detection and isolation of modular dynamic systems modeled as sets of place-bordered Petri nets. The common places among the set of Petri nets modeling a system capture coupling of various system components. The transitions are labeled by events, some of which are unobservable, i.e., not directly recorded by the sensors attached to the system. The events whose occurrence must be diagnosed have unobservable transition labels. These events model faults or other significant changes in the system state. The existing theory of diagnosis of discrete-event systems is extended in the context of the above model. The modular structure of the system is exploited by a distributed algorithm for fault diagnosis. A Petri net diagnoser is associated to every Petri net and the diagnosers communicate in real-time during the diagnostic process when the token count of common places changes. A merge function is defined to combine the individual diagnoser states and recover the complete diagnoser state that would be obtained under a monolithic approach. Strategies that reduce the communication overhead are presented. The software implementation of the distributed algorithm is discussed.Note to practitioner -In the last decade monitoring, fault detection, and diagnosis methodologies based on the use of discrete-event models have been successfully used in a variety of technological systems ranging from document processing systems to intelligent transportation systems. This paper was motivated by the problem of fault diagnosis for modular (distributed) dynamic discreteevent systems (DES). As a DES modeling formalism, Petri nets offer potential advantages in terms of the distributed representation of the system and of the ability to represent coupling of the system components. The systems studied in this paper are sets of modules coupled with each other through various system components and modeled using Petri nets. We present a distributed fault diagnosis algorithm which allows each module in the distributed system to diagnose its faults independently unless completion of a task requires the use of coupled components.

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“…Presence of limited sensing capabilities can lead to ambiguity in knowing the system state and thereby ambiguity in decision-making. Consider for example the problem of decentralized diagnosis [3], [9], [11], [1], [12], [5], [13] of discrete event systems (DESs). Suppose there exist two traces that are executable in the plant and are indistinguishable to a local diagnoser, and one of the traces is a "failure trace" while the other one is a "non-failure" trace.…”

Section: Introductionmentioning

confidence: 99%

Inference-Based Ambiguity Management in Decentralized Decision-Making: Decentralized Control of Discrete Event Systems

Kumar

Takai

2007

IEEE Trans. Automat. Contr.

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Abstract-The task of decentralized decision-making involves interaction of a set of local decision-makers, each of which operates under limited sensing capabilities and is thus subjected to ambiguity during the process of decision-making. In a prior work [4] we made a key observation that such ambiguities are of differing gradations and presented a framework for inferencing over various local control decisions of varying ambiguity levels to arrive at a global control decision. We develop a similar framework for performing diagnosis in a decentralized setting. For each event-trace executed by a system being monitored, each local diagnoser issues its own diagnosis decision (failure or non-failure or unsure), tagged with a certain ambiguity level (zero being the minimum). A global diagnosis decision is taken to be a "winning" local diagnosis decision, i.e., one with a minimum ambiguity level. The computation of an ambiguity level for a local decision requires an assessment of the self-ambiguities as well as the ambiguities of the others, and an inference based up on such knowledge. In order to characterize the class of systems for which any fault can be detected within a uniformly bounded delay, we introduce the notion of N -inference-diagnosability (for failures), where the index N represents the maximum ambiguity level of any winning local decision. We show that the codiagnosability introduced in [5] is the same as 0-inferencediagnosability; the conditional codiagnosability introduced in [13] is a type of 1-inference-diagnosability; and the class of higher-index inference-diagnosable systems strictly subsumes the class of lower-index ones

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Distributed diagnosis for qualitative systems

Cited by 58 publications

References 8 publications

Modular Fault Diagnosis Based on Discrete Event Systems

Modular Fault Diagnosis Based on Discrete Event Systems

Distributed Diagnosis of Place-Bordered Petri Nets

Inference-Based Ambiguity Management in Decentralized Decision-Making: Decentralized Control of Discrete Event Systems

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