Polynomial verification for safe codiagnosability of decentralized fuzzy discrete-event systems

Since fuzzy discrete-event systems (FDESs) modeled by fuzzy automata were put forward, extensive research on FDESs has been successfully conducted from different perspectives. Recently, the safe codiagnosability of decentralized FDESs was introduced and an approach of constructing the safe codiagnos...

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Vydáno v:Fuzzy sets and systems Ročník 490; s. 109041
Hlavní autoři: Liu, Fuchun, Cao, Weihua, Dziong, Zbigniew
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 15.08.2024
Témata:
Decentralized systems
Discrete-event systems
Fuzzy automata
Polynomial algorithm
Safe failure diagnosis
Safe failure diagnosis
Discrete-event systems
Fuzzy automata
Polynomial algorithm
Decentralized systems
ISSN:0165-0114, 1872-6801
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Shrnutí:Since fuzzy discrete-event systems (FDESs) modeled by fuzzy automata were put forward, extensive research on FDESs has been successfully conducted from different perspectives. Recently, the safe codiagnosability of decentralized FDESs was introduced and an approach of constructing the safe codiagnoser to verify the safe codiagnosability was proposed. However, the complexity of constructing the safe codiagnoser of decentralized FDESs is exponential. In this paper, we present a polynomial verification. Firstly, the recognizer and the safe coverifier are constructed to recognize the prohibited strings in the illegal language and carry out safe diagnosis of decentralized FDESs, respectively. Then the necessary and sufficient condition for safe codiagnosability of decentralized FDESs is presented. In particular, an algorithm for verifying the safe codiagnosability of decentralized FDESs is proposed based on the safe coverifier. Notably, both complexities of constructing the safe coverifier and verifying the safe codiagnosability are polynomial in the numbers of fuzzy events and fuzzy states of FDESs. Finally, two examples are provided to illustrate the proposed algorithm and the derived results.
ISSN:0165-0114
1872-6801
DOI:10.1016/j.fss.2024.109041