Minimal Diagnosis and Diagnosability of Discrete-Event Systems Modeled by Automata
In the last several decades, the model-based diagnosis of discrete-event systems (DESs) has increasingly become an active research topic in both control engineering and artificial intelligence. However, in contrast with the widely applied minimal diagnosis of static systems, in most approaches to th...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/4306261 |
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| author | Xiangfu Zhao Gianfranco Lamperti Dantong Ouyang Xiangrong Tong |
| author_facet | Xiangfu Zhao Gianfranco Lamperti Dantong Ouyang Xiangrong Tong |
| author_sort | Xiangfu Zhao |
| collection | DOAJ |
| description | In the last several decades, the model-based diagnosis of discrete-event systems (DESs) has increasingly become an active research topic in both control engineering and artificial intelligence. However, in contrast with the widely applied minimal diagnosis of static systems, in most approaches to the diagnosis of DESs, all possible candidate diagnoses are computed, including nonminimal candidates, which may cause intractable complexity when the number of nonminimal diagnoses is very large. According to the principle of parsimony and the principle of joint-probability distribution, generally, the minimal diagnosis of DESs is preferable to a nonminimal diagnosis. To generate more likely diagnoses, the notion of the minimal diagnosis of DESs is presented, which is supported by a minimal diagnoser for the generation of minimal diagnoses. Moreover, to either strongly or weakly decide whether a minimal set of faulty events has definitely occurred or not, two notions of minimal diagnosability are proposed. Necessary and sufficient conditions for determining the minimal diagnosability of DESs are proven. The relationships between the two types of minimal diagnosability and the classical diagnosability are analysed in depth. |
| format | Article |
| id | doaj-art-319bdcef57054cc684bbcd3553dbbac3 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-319bdcef57054cc684bbcd3553dbbac32025-02-03T01:01:30ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/43062614306261Minimal Diagnosis and Diagnosability of Discrete-Event Systems Modeled by AutomataXiangfu Zhao0Gianfranco Lamperti1Dantong Ouyang2Xiangrong Tong3School of Computer and Control Engineering, Yantai University, Yantai 264005, ChinaDepartment of Information Engineering, University of Brescia, Brescia 25123, ItalyCollege of Computer Science and Technology, Jilin University, Changchun 130012, ChinaSchool of Computer and Control Engineering, Yantai University, Yantai 264005, ChinaIn the last several decades, the model-based diagnosis of discrete-event systems (DESs) has increasingly become an active research topic in both control engineering and artificial intelligence. However, in contrast with the widely applied minimal diagnosis of static systems, in most approaches to the diagnosis of DESs, all possible candidate diagnoses are computed, including nonminimal candidates, which may cause intractable complexity when the number of nonminimal diagnoses is very large. According to the principle of parsimony and the principle of joint-probability distribution, generally, the minimal diagnosis of DESs is preferable to a nonminimal diagnosis. To generate more likely diagnoses, the notion of the minimal diagnosis of DESs is presented, which is supported by a minimal diagnoser for the generation of minimal diagnoses. Moreover, to either strongly or weakly decide whether a minimal set of faulty events has definitely occurred or not, two notions of minimal diagnosability are proposed. Necessary and sufficient conditions for determining the minimal diagnosability of DESs are proven. The relationships between the two types of minimal diagnosability and the classical diagnosability are analysed in depth.http://dx.doi.org/10.1155/2020/4306261 |
| spellingShingle | Xiangfu Zhao Gianfranco Lamperti Dantong Ouyang Xiangrong Tong Minimal Diagnosis and Diagnosability of Discrete-Event Systems Modeled by Automata Complexity |
| title | Minimal Diagnosis and Diagnosability of Discrete-Event Systems Modeled by Automata |
| title_full | Minimal Diagnosis and Diagnosability of Discrete-Event Systems Modeled by Automata |
| title_fullStr | Minimal Diagnosis and Diagnosability of Discrete-Event Systems Modeled by Automata |
| title_full_unstemmed | Minimal Diagnosis and Diagnosability of Discrete-Event Systems Modeled by Automata |
| title_short | Minimal Diagnosis and Diagnosability of Discrete-Event Systems Modeled by Automata |
| title_sort | minimal diagnosis and diagnosability of discrete event systems modeled by automata |
| url | http://dx.doi.org/10.1155/2020/4306261 |
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