Diagnosers for discrete event systems: improved realization and examples

Kart, Bora Eser
Many complex systems in different areas such as manufacturing, telecommunications or transportation can be modeled as Discrete Event Systems (DES). The task of fault detection and isolation is naturally desired for every system that has the possibility of any fault occurrences in it. To this end, a DES machine that can detect every modeled fault after a bounded number of event occurrence called diagnoser is used. In this thesis, there are two diagnoser realizations corresponding to the notions of event and language diagnosability. The proposed diagnosers function as centralized diagnosers that run parallel to the given systems and perform online diagnosis. Differing from similar studies, we denote our diagnosers as improved diagnosers because they explicitly give a notification as soon as a faulty behavior is detected. This makes our diagnosers more useful in practice. In addition, our study simplifies the computation of the worst-case delay until a fault is detected. Moreover, we further enhance our improved diagnoser by applying an algorithm to remove unnecessary observations. As a result, fewer sensors are needed and the constructed diagnosers have a smaller size. The merits of the proposed diagnoser approach and the applicability of our algorithmic implementation are demonstrated by a communication network system example.


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Citation Formats
B. E. Kart, “Diagnosers for discrete event systems: improved realization and examples,” M.S. - Master of Science, Middle East Technical University, 2014.