Chengzong Li;Yufeng Chen;Almetwally M. Mostafa;Mohamed Khalgui
{"title":"基于标记Petri网模型的离散事件系统可诊断性监督控制","authors":"Chengzong Li;Yufeng Chen;Almetwally M. Mostafa;Mohamed Khalgui","doi":"10.1109/TASE.2025.3554353","DOIUrl":null,"url":null,"abstract":"This paper proposes an active fault diagnosis method to enforce the diagnosability of discrete event systems using labeled Petri nets by constructing a diagnostic supervisor. For a non-diagnosable net model, its diagnosability is viewed as a control specification and addressed by using supervisory control techniques. First, an event-based monitor and a Petri net structure, referred to as data isolation arcs, are introduced to apply control specifications for labeled Petri nets. Then, a diagnostic supervisor reachability graph is generated to estimate the current state of the diagnoser. By analyzing the diagnostic supervisor reachability graph, an integer linear programming model is formulated to design a diagnostic supervisor, which can prevent the system from entering into any indeterminate cycle only by observing the occurrence of events. Finally, by the obtained diagnostic supervisor, the resulting net model is shown to be diagnosable. Some examples are presented to demonstrate the proposed method. Note to Practitioners—Faults have a significant impact on the normal operation of a system, and timely detection and isolation are crucial to ensuring system stability and production efficiency. Nevertheless, in certain systems, the occurrence of faults cannot be determined by a finite number of observations. To address this problem, this work introduces an active fault diagnosis method in the framework of labeled Petri nets, aiming to enforce the diagnosability of a system. The diagnosability condition is treated as a control specification such that it is readily accessible for practitioners to construct a diagnostic supervisor with Petri nets by following a typical and traditional control paradigm, which ensures that the controlled system is diagnosable.","PeriodicalId":51060,"journal":{"name":"IEEE Transactions on Automation Science and Engineering","volume":"22 ","pages":"13855-13870"},"PeriodicalIF":6.4000,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Supervisory Control of Discrete Event Systems Modeled With Labeled Petri Nets for Diagnosability Enforcement\",\"authors\":\"Chengzong Li;Yufeng Chen;Almetwally M. Mostafa;Mohamed Khalgui\",\"doi\":\"10.1109/TASE.2025.3554353\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes an active fault diagnosis method to enforce the diagnosability of discrete event systems using labeled Petri nets by constructing a diagnostic supervisor. For a non-diagnosable net model, its diagnosability is viewed as a control specification and addressed by using supervisory control techniques. First, an event-based monitor and a Petri net structure, referred to as data isolation arcs, are introduced to apply control specifications for labeled Petri nets. Then, a diagnostic supervisor reachability graph is generated to estimate the current state of the diagnoser. By analyzing the diagnostic supervisor reachability graph, an integer linear programming model is formulated to design a diagnostic supervisor, which can prevent the system from entering into any indeterminate cycle only by observing the occurrence of events. Finally, by the obtained diagnostic supervisor, the resulting net model is shown to be diagnosable. Some examples are presented to demonstrate the proposed method. Note to Practitioners—Faults have a significant impact on the normal operation of a system, and timely detection and isolation are crucial to ensuring system stability and production efficiency. Nevertheless, in certain systems, the occurrence of faults cannot be determined by a finite number of observations. To address this problem, this work introduces an active fault diagnosis method in the framework of labeled Petri nets, aiming to enforce the diagnosability of a system. The diagnosability condition is treated as a control specification such that it is readily accessible for practitioners to construct a diagnostic supervisor with Petri nets by following a typical and traditional control paradigm, which ensures that the controlled system is diagnosable.\",\"PeriodicalId\":51060,\"journal\":{\"name\":\"IEEE Transactions on Automation Science and Engineering\",\"volume\":\"22 \",\"pages\":\"13855-13870\"},\"PeriodicalIF\":6.4000,\"publicationDate\":\"2025-03-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Automation Science and Engineering\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10938260/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Automation Science and Engineering","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10938260/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Supervisory Control of Discrete Event Systems Modeled With Labeled Petri Nets for Diagnosability Enforcement
This paper proposes an active fault diagnosis method to enforce the diagnosability of discrete event systems using labeled Petri nets by constructing a diagnostic supervisor. For a non-diagnosable net model, its diagnosability is viewed as a control specification and addressed by using supervisory control techniques. First, an event-based monitor and a Petri net structure, referred to as data isolation arcs, are introduced to apply control specifications for labeled Petri nets. Then, a diagnostic supervisor reachability graph is generated to estimate the current state of the diagnoser. By analyzing the diagnostic supervisor reachability graph, an integer linear programming model is formulated to design a diagnostic supervisor, which can prevent the system from entering into any indeterminate cycle only by observing the occurrence of events. Finally, by the obtained diagnostic supervisor, the resulting net model is shown to be diagnosable. Some examples are presented to demonstrate the proposed method. Note to Practitioners—Faults have a significant impact on the normal operation of a system, and timely detection and isolation are crucial to ensuring system stability and production efficiency. Nevertheless, in certain systems, the occurrence of faults cannot be determined by a finite number of observations. To address this problem, this work introduces an active fault diagnosis method in the framework of labeled Petri nets, aiming to enforce the diagnosability of a system. The diagnosability condition is treated as a control specification such that it is readily accessible for practitioners to construct a diagnostic supervisor with Petri nets by following a typical and traditional control paradigm, which ensures that the controlled system is diagnosable.
期刊介绍:
The IEEE Transactions on Automation Science and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. T-ASE welcomes results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, security, service, supply chains, and transportation. T-ASE addresses a research community willing to integrate knowledge across disciplines and industries. For this purpose, each paper includes a Note to Practitioners that summarizes how its results can be applied or how they might be extended to apply in practice.