An Efficient Approach for Online Diagnosis of Discrete Event Systems

Basile, Francesco; Chiacchio, Pasquale; Tommasi, G. De

doi:10.1109/tac.2009.2014932

Cited by 158 publications

(83 citation statements)

References 21 publications

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“…In fact when w = ε the j-vector associated to node M 0 , [0] is [0], hence the diagnosis state is ∆(ε, T f 1 ) = 0. On the contrary, after w = t 1 t 2 fires we reach the same basis marking M 0 , [0] but now its j-vector is [1], and the diagnosis state is changed to ∆(t 1 t 2 , T f 1 ) = 3.…”

Section: Basis Reachability Graphmentioning

confidence: 99%

“…Thus, there exists a sequence containing a transition t f ∈ T i f firable at M on the unobservable subnet if and only if e 1 , t e Note that, by looking at the BRG we can also read all sequences of observable words, that is finite in the case at hand, and equal to {ε, t 1 , t 1 t 2 , t 1 t 2 t 2 }. Moreover note that for all the j-vectors in Table 2 the component associated to ε 12 is equal to 0.…”

Section: Corollary 43 Consider An Observed Word W ∈ T *mentioning

confidence: 99%

“…In [2] Benveniste et al present a net unfolding approach for designing an on-line asynchronous diagnoser. In [1] Basile et al present a diagnosis approach where the diagnoser is built on-line by defining and solving integer linear programming problems. In [8], in order to avoid the redesign and the redefinition of the diagnoser when the structure of the system changes, Dotoli et al propose a diagnoser that works on-line.…”

Section: Introductionmentioning

confidence: 99%

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Fault detection for discrete event systems using Petri nets with unobservable transitions

2010

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In this paper we present a fault detection approach for discrete event systems using Petri nets. We assume that some of the transitions of the net are unobservable, including all those transitions that model faulty behaviors. Our diagnosis approach is based on the notions of basis marking and justification, that allow us to characterize the set of markings that are consistent with the actual observation, and the set of unobservable transitions whose firing enable it. This approach applies to all net systems whose unobservable subnet is acyclic. If the net system is also bounded the proposed approach may be significantly simplified by moving the most burdensome part of the procedure off-line, thanks to the construction of a graph, called the basis reachability graph.

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Section: Basis Reachability Graphmentioning

confidence: 99%

Section: Corollary 43 Consider An Observed Word W ∈ T *mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fault detection for discrete event systems using Petri nets with unobservable transitions

2010

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“…Extending the proposed scheme to more complex problems is our future work. Furthermore, the malfunction of sensors, actuators, and erroneous actions of human operators can have some disastrous consequences in high risk systems [24][25][26][27]. These faults can lead to undesirable actions.…”

Section: Viiconclusionmentioning

confidence: 99%

Modelling and Control of KRC Systems Using TPN and TA

Allaa¹,

Awad²,

Anwar³

et al. 2015

IJAREEIE

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This paper models and supervises kernel railroad crossing (KRC) systems using timed Petri nets and focuses on the control synthesis method, which consists in computing new firing conditions for the timed automaton (TA) transitions so that the forbidden locations are no longer reachable. The system to be modeled and supervised using timed Petri nets is converted to a TA and is analyzed using automata so that the functioning of the system respects given specifications. The main reason of using automata is that although the timed Petri nets supervisor controls the system, it fails to define the time units needed for the undefined time of a transition. Simulation results show the soundness of KRC modeling and supervision in the sense of ensuring the safety and maximizing utility (the gate should be opened as long as possible). KEYWORDS:Automata, Timed automata, discrete event systems, Petri nets, Timed Petri nets, KRC systems I.INTRODUCTIONThe process synchronization and forbidden states avoidance are considered as the main problems in both normal and abnormal modes of automation systems [1]. These characteristics allow the system to be considered as Discrete Event System (DES) and allow the researchers to perform the analysis and control of such systems using Petri nets (PN) and automata. DES is a dynamic system with state evolution produced by the occurrence of physical events. For example, an event is opening or closing a gate in Kernel Railroad Crossing (KRC) systems [2][3]. DES can be found in domains such as manufacturing, robotic, traffic control, logistics, and communication systems, etc.Important contributions in supervisory control of DES based on the Finite Automata (FA) and Petri Nets (PNs) are found in [4][5][6][7][8]. Petri net models are normally more compact than similar automata based models and are better suited for the representation of discrete event systems. They also have a good representational power [9]. On one hand, numerous approaches to the systematic construction of Petri net models have been proposed in [10]. On the other hand, because automata detail the process to be modelled, they are also employed to analysis and avoid forbidden states with ease.Historically, the theory of DES for supervision was initiated by the research work of Ramadge and Wonham [8]. A process is considered to be a spontaneous generator of events. Its functioning is characterized by event sequences. A supervisor is a DES which can modify the functioning of the process in order to avoid forbidden states. Unfortunately, the theory of Ramadge and Wonham does not a maximally permissive in nature [11]. A maximal permissive supervisor is to ensure that the controlled behaviour of the DES must be maximally permissive within a given specifications, i.e. all events which do not contradict the given specifications are allowed to happen. Thus, the theory of Ramadge and Wonham cannot be used to control all DES. An extension of this theory to the control of DES is proposed to force the occurrence of certain events to...

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“…But the computational effort to run a diagnoser is higher than in the case of the compiled diagnoser, and it is difficult to derive a diagnosability test. In Petri Nets framework [5], the on-line fault detection strategy can avoid redesigning and redefining the diagnoser upon a variation in the system structure, this algorithm does not require off-line calculations based on the structure of the considered PN system.…”

Section: Introductionmentioning

confidence: 99%

Online Fault Diagnoser for Partially Observed Petri Nets

Peng¹,

Liu²,

Jiancheng³

et al. 2016

dteees

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Abstract. This paper investigates the fault detection problem for Discrete Event Systems which can be modeled by Partially Observed Petri Nets (POPN). To overcome the shortage of the low diagnosability of the currently POPN online fault diagnoser, we propose an improved on-line fault diagnosis algorithm that integrates Generalized Mutual Exclusion Constraints(GMEC) and Integer Linear Programming (ILP). We assume that the POPN structure and its initial markings are known, the faults are modeled as unobservable transitions. First, the event sequence is observed and recorded. The ILP problem of POPN is solved for elementary diagnosis for the system behavior. While the system is diagnosed that some faults may have happened, we use the GMEC for the further diagnosis. Finally, a real discrete event system is taken as an example, we model and analyse the discrete event system, the proposed algorithm increases the diagnosablity remarkably.

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An Efficient Approach for Online Diagnosis of Discrete Event Systems

Cited by 158 publications

References 21 publications

Fault detection for discrete event systems using Petri nets with unobservable transitions

Fault detection for discrete event systems using Petri nets with unobservable transitions

Modelling and Control of KRC Systems Using TPN and TA

Online Fault Diagnoser for Partially Observed Petri Nets

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