Scopus İndeksli Yayınlar Koleksiyonu

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  • Conference Object
    Computation of Projections for the Abstraction-Based Diagnosability Verification
    (IFAC Secretariat, 2010) Schmidt, K.
    The verification of language-diagnosability (LD) for discrete event systems (DES) generally requires the explicit evaluation of the overall system model which is infeasible for practical systems. In order to circumvent this problem, our previous work proposes the abstraction-based LD verification using natural projections that fulfill the loop-preserving observer (LPO) property. In this paper, we develop algorithms for the verification and computation of such natural projections. We first present a polynomial-time algorithm that allows to test if a given natural projection is a loop-preserving observer. Then, we show that, in case the LPO property is violated, finding a minimal extension of the projection alphabet such that the LPO condition holds is NP-hard. Finally, we adapt a polynomial-time heuristic algorithm by Feng and Wonham for the efficient computation of loop-preserving observers.
  • Article
    Citation - WoS: 12
    Citation - Scopus: 17
    Abstraction-Based Verification of Codiagnosability for Discrete Event Systems
    (Pergamon-elsevier Science Ltd, 2010) Schmidt, K.
    In this paper, we investigate the verification of codiagnosability for discrete event systems (DES). That is, it is desired to ascertain if the occurrence of system faults can be detected based on the information of multiple local sites that partially observe the overall DES. As an improvement of existing codiagnosability tests that resort to the original DES with a potentially computationally infeasible state space, we propose a method that employs an abstracted system model on a smaller state space for the codiagnosability verification. Furthermore, we show that this abstraction can be computed without explicitly evaluating the state space of the original model in the practical case where the DES is composed of multiple subsystems. (c) 2010 Elsevier Ltd. All rights reserved.