Decentralized prognosis of fuzzy discrete-event systems

被引：0

作者：

Benmessahel, B. ^{[1
]}

Touahria, M. ^{[1
]}

Nouioua, F. ^{[2
]}

Gaber, J. ^{[3
]}

Lorenz, P. ^{[4
]}

机构：

[1] Univ Ferhat Abbas Setif 1, Comp Sci Dept, Pole 2 El Bez, Setif 19000, Algeria

[2] Aix Marseille Univ, CNRS, ENSAM, Univ Toulon,LSIS UMR 7296, Marseille, France

[3] Aix Marseille Univ, Univ Technol Belft Montbeliard, Rue Thierry Mieg, F-90010 Belfort, France

[4] Univ Haute Alsace, IUT, Comp Sci Dept, Colmar, France

来源：

IRANIAN JOURNAL OF FUZZY SYSTEMS | 2019年 / 16卷 / 03期

关键词：

Co-predictability; Discrete-event systems; Decentralized prognosis; Failure detection; Fuzzy automata; Fuzzy systems; SUPERVISORY CONTROL; OBSERVABILITY; INFORMATION;

D O I：

暂无

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper gives a decentralized approach to the problem of failure prognosis in the framework of fuzzy discrete event systems (FDES). A notion of co-predictability is formalized for decentralized prognosis of FDESs, where several local agents with fuzzy observability rather than crisp observability are used in the prognosis task. An FDES is said to be co-predictable if each faulty event can be predicted prior to its occurrence by at least one local agent using the observability of fuzzy events. The verification of the decentralized predictability is performed by constructing a fuzzy co-verifier from a given FDES. The complexity of the fuzzy co-verifier is polynomial with respect to the FDES being predicted, and is exponential with respect to the number of the local prognosis agents. Then, a necessary and sufficient condition for the co-predictability of FDESs is given. In addition, we show that the proposed method may be used to deal with the decentralized prognosis for both FDESs and crisp DESs. Finally, to illustrate the effectiveness of the approach, some examples are provided.

引用

页码：127 / 143

页数：17

共 44 条

[1] Observability and decentralized control of fuzzy discrete-event systems [J].

Cao, YZ ;

Ying, MS .

IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2006, 14 (02) :202-216

[2] Supervisory control of fuzzy discrete event systems [J].

Cao, YZ ;

Ying, MS .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2005, 35 (02) :366-371

[3]

Cassandras C.G., 2010, Introduction to Discrete Event Systems, DOI [10.1007/978-3-030-72274-6, DOI 10.1007/978-3-030-72274-6]

[4]

Cassez Franck, 2013, Formal Modeling and Analysis of Timed Systems. Proceedings of 11th International Conference (FORMATS 2013): LNCS 8053, P62, DOI 10.1007/978-3-642-40229-6_5

[5] ON FAULT PREDICTABILITY IN STOCHASTIC DISCRETE EVENT SYSTEMS [J].

Chang, Ming ;

Dong, Wei ;

Ji, Yindong ;

Tong, Lang .

ASIAN JOURNAL OF CONTROL, 2013, 15 (05) :1458-1467

[6] Stochastic Failure Prognosability of Discrete Event Systems [J].

Chen, Jun ;

Kumar, Ratnesh .

IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2015, 60 (06) :1570-1581

[7] Predictability of event occurrences in partially-observed discrete-event systems [J].

Genc, Sahika ;

Lafortune, Stephane .

AUTOMATICA, 2009, 45 (02) :301-311

[8] Behavior-modulation technique in mobile robotics using fuzzy discrete event system [J].

Huq, Rajibul ;

Mann, George K. I. ;

Gosine, Raymond G. .

IEEE TRANSACTIONS ON ROBOTICS, 2006, 22 (05) :903-916

[9] Distributed fuzzy discrete event system for robotic sensory information processing [J].

Huq, Rajibul ;

Mann, George K. I. ;

Gosine, Raymond G. .

EXPERT SYSTEMS, 2006, 23 (05) :273-289

[10] Behavior Coordination of Mobile Robotics Using Supervisory Control of Fuzzy Discrete Event Systems [J].

Jayasiri, Awantha ;

Mann, George K. I. ;

Gosine, Raymond G. .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2011, 41 (05) :1224-1238

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