Failures In Discrete Event Systems Research Articles

Failures in discrete-event systems and dealing with them by means of Petri nets

An approach based on Petri nets pointing to the manner how to deal with failures in discrete-event systems is presented. It uses the reachability tree and/or reachability graph of the Petri net-based model of the real system as well as the synthesis of a supervisor to remove the possible deadlock(s). To illustrate the applicability of the approach to the detection and recovery of failures in DES modelled by Petri nets the case study on a railroad crossing is introduced.

Conjunctive and Disjunctive Architectures for Decentralized Prognosis of Failures in Discrete-Event Systems

Kumar and Takai have proposed an architecture for the decentralized prognosis of discrete-event systems (DES), where several local prognosers cooperate to predict failures in a DES. In this paper, we first present the proposition (Kumar and Takai, Decentralized prognosis of failures in discrete event systems, IEEE Trans. Autom. Control, vol. 55, no. 1, pp. 48-59, Jan. 2010) as a disjunctive architecture, and then we develop a conjunctive architecture which is dual and complementary to the disjunctive one. We also propose a mixed architecture that combines and generalizes the disjunctive and conjunctive architectures. We finally show that our work can be easily extended to predict a failure at least k steps before its occurrence, for a given k >; 1.

Decentralized Prognosis of Failures in Discrete Event Systems

We study the prognosis of failures, i.e., their prediction prior to their occurrence, in discrete event systems in a decentralized setting where multiple prognosers use their local observations to issue local prognosis decisions. We define the notion of correctness of a decentralized set of prognosers in terms of ?no missed detections? (each failure is prognosed prior to its occurrence) and ?no false alarms? (an incorrect prognostic decision is never issued), and introduce the notion of <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">coprognosability</i> as an existence condition. When specialized to the centralized case (i.e., the case of a single prognoser), this condition turns out to be weaker than the one introduced by Genc and Lafortune in 2006 since a uniform bound on the number of steps within which a failure will occur is not required. For comparison, we also introduce the stronger notion of ?uniformly bounded coprognosability? and identify the subclass of decentralized prognosers for which it serves as an existence condition. We show that the two notions coincide when the underlying system and its nonfailure specification possess finite-state representations, and present a verification algorithm whose complexity is polynomial in the sizes of the system being prognosed and its nonfailure specification, and is exponential in the number of the local prognosers. We also introduce the notion of <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">reaction bound for coprognosis</i> as the earliest time beyond a prognostic decision when a failure can occur, and present an algorithm for computing it. The complexity of this algorithm is identical to that of the verification algorithm. An algorithm with complexity linear in the size of the specification and the number of local prognosers is also presented for an online prognosis of failures. We show that the notions of coprognosability and its uniformly bounded version are in general incomparable with the notion of <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">codiagnosability</i> (that guarantees a uniformly bounded delay detection of a failure by a local diagnoser). When the system cannot execute an unbounded sequence of unobservable events, uniformly bounded coprognosability implies codiagnosability, whereas coprognosability and codiagnosability remain incomparable.

Diagnosis of repeated failures for discrete event systems with linear-time temporal-logic specifications

In our earlier work, we introduced a state-based approach for the diagnosis of repeatedly occurring failures in discrete event systems (DESs). Since temporal logic provides a simpler way of specifying system properties; in this paper, a temporal-logic-based approach for diagnosing the occurrence of a repeated number of failures is developed. Linear-time temporal-logic (LTL) formulae are used to represent the specifications of DESs. Notions of prediagnosability for failures and diagnosability for repeated failures are introduced in the setting of temporal logic. A polynomial algorithm for the test of prediagnosability for failures is provided. The diagnosis problem for repeated failures in the temporal-logic setting is reduced to one in a state-based setting, and so the prior results of a state-based repeated failure diagnosis can be applied. Finally, a simple example is given for illustration. Note to Practitioners-Certain failures in a system are repeatable, such as routing errors in a manufacturing system. A theory for the diagnosis of such failures was presented in an earlier work of Jiang et al. The present paper uses temporal logic to specify such failures. It turns out that repeatable failures can be specified as violations of invariant properties (i.e., properties that must always hold). Given an invariant property that the system must always satisfy, an algorithm is presented to refine the system model and label those states of the refined system where the property is violated. The problem of repeated diagnosis then requires determining, within a bounded delay, each time a "failure-state" is visited. For this analysis, the existing theory developed by Jiang et al. is used.

Diagnosis of repeated/intermittent failures in discrete event systems

We introduce the notion of repeated failure diagnosability for diagnosing the occurrence of a repeated number of failures in discrete event systems. This generalizes the earlier notion of diagnosability that was used to diagnose the occurrence of a failure, but from which the information regarding the multiplicity of the occurrence of the failure could not be obtained. It is possible that in some systems the same type of failure repeats a multiple number of times. It is desirable to have a diagnoser which not only diagnoses that such a failure has occurred, but also determines the number of times the failure has occurred. To aid such analysis we introduce the notions of K-diagnosability (K failures diagnosability), [1, K]-diagnosability (1 through K failures diagnosability), and [1, /spl infin/]-diagnosability (1 through /spl infin/ failures diagnosability). Here the first (resp., last) notion is the weakest (resp., strongest) of all three and the earlier notion of diagnosability is the same as that of K-diagnosability or that of [1, K]-diagnosability with K=1. We give polynomial algorithms for checking these various notions of repeated failure diagnosability and also present a procedure of polynomial complexity for the online diagnosis of repeated failures.

Robust and fault-tolerant supervisory control of discrete event systems with partial observation and model uncertainty

This paper proposes the notions of faults and failures in discrete event systems (DESs) with partial observation. They are associated with controllability and an observability property. The proposed notions are used to address the notion of tolerable fault event sequences which represents fault-tolerant behaviour of systems as a desired specification. A robust and fault-tolerant supervisor is a controller which is robust to model uncertainty and guarantees fault-tolerant behaviour of a system. In this paper we present necessary and sufficient conditions for the existence of a robust and fault-tolerant supervisor. The developed conditions capture the concepts of controllability and observability which are cores in the control of DESs with partial observation