Failure Predictability of Stochastic Discrete Event Systems

Ye Bin-bin; Liu Fu-chun

doi:10.12052/gdutxb.180030

English Version Journal Login

您当前的位置：

首页 >

文章列表页 >

Failure Predictability of Stochastic Discrete Event Systems

更新时间：2026-05-27

- Failure Predictability of Stochastic Discrete Event Systems
- Vol. 35, Issue 6, Pages: 83-89(2018)
- 作者机构：
  
  广东工业大学　计算机学院,广东,广州,510006
- 作者简介：
- 基金信息：
- DOI：10.12052/gdutxb.180030
  CLC： TP301.1
- Online First：23 November 2018，
  
  Published：2018
- 稿件说明：
移动端阅览
叶彬彬, 刘富春. 随机离散事件系统的故障预测[J]. 广东工业大学学报, 2018, 35(6): 83-89.

Ye Bin-bin, Liu Fu-chun. Failure Predictability of Stochastic Discrete Event Systems[J]. 2018, 35(6): 83-89.
叶彬彬, 刘富春. 随机离散事件系统的故障预测[J]. 广东工业大学学报, 2018, 35(6): 83-89. DOI： 10.12052/gdutxb.180030.

Ye Bin-bin, Liu Fu-chun. Failure Predictability of Stochastic Discrete Event Systems[J]. 2018, 35(6): 83-89. DOI： 10.12052/gdutxb.180030.

摘要

针对随机系统模型

提出一种随机离散事件系统的故障预测方法. 先对随机离散事件系统的故障可预测性进行形式化

再通过引入概率转移矩阵构建一个故障预测器自动机

得到关于随机离散事件系统的故障可预测性的充分必要条件. 由此

在故障预测器的基础上

通过计算其扩展马尔可夫矩阵

可判定随机离散事件系统是否具有故障可预测性

从而实现对故障事件在其发生之前的准确预测.

Abstract

An approach for failure prediction for stochastic DESs modeled by stochastic finite state automata is proposed. Firstly

the notion of predictability of failure events of stochastic systems is formalized. Then a predictor automaton is constructed by introducing the probability transition matrix

and a necessary and sufficient condition of the predictability of stochastic systems is presented. Based on the fault predictor

a method for checking whether the considered stochastic DES has been equipped with the capability of failure prediction is developed by computing the extended Markov matrix

which results in the realization of accurate prediction of the failure events before occurring.

关键词

Keywords

references

SAMPATH M, SENGUPTA R, LAFORTUNE S, et al . Diagnosability of discrete-event systems [J ] . IEEE Transactions on Automatic Control, 1995, 40(9): 1555-1575.

ZAYTOON J, LAFORTUNE S. Overview of fault diagnosis methods for discrete event systems [J]. Annual Reviews in Control, 2013, 37(2): 308-320.

QIU W, KUMAR R. Decentralized failure diagnosis of discrete event systems [J]. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 2006, 36(2): 384-395.

CHEN Z, LIN F, WANG C, et al . Active diagnosability of discrete event systems and its application to battery fault diagnosis [J ] . IEEE Transact ions on Control Systems Technology, 2014, 22(5): 1892-1898.

KWONG R H, YONGEMALLO D L. Fault diagnosis in discrete event systems with incomplete models: learnability and diagnosability [J]. IEEE Transactions on Cybernetics, 2015, 45(7): 1236-1249.

WANG X Y, OUYANG D T, ZHAO J. Discrete-event system diagnosis upon incomplete model [J]. Journal of Software, 2012, 23(3): 465-475.

ZHANG J, KHALGUI M, LI Z, et al . Reconfigurable coordination of distributed discrete event control systems [J ] . IEEE Transactions on Control Systems Technology, 2015, 23(1): 323-330.

LIU F, QIU D. Diagnosability of fuzzy discrete-event systems: a fuzzy approach [J]. IEEE Transactions on Fuzzy Systems, 2006, 17(2): 372-384.

GENC S, LAFORTUNE S. Predictability of event occurrences in partially-observed discrete-event systems [J]. Automatica, 2009, 45(2): 301-311.

TAKAI S, KUMAR R. Distributed failure prognosis of discrete event systems with bounded-delay communications [J]. IEEE Transactions on Automatic Control, 2012, 57(5): 1259-1265.

KHOUMSI A, CHAKIB H. Conjunctive and disjunctive architectures for decentralized prognosis of failures in discrete-event systems [J]. IEEE Transactions on Automation Science Engineering, 2012, 9(2): 412-417.

NUÑO-SÁNCHEZ S A, RAMÍREZ-TREVIÑO A, RUIZ-LEÓN J. Structural sequence detectability in free choice interpreted petri nets [J]. IEEE Transactions on Automatic Control, 2016, 61(1): 198-203.

SHU S, HUANG Z, LIN F. Online sensor activation for detectability of discrete event systems [J]. IEEE Trans- actions on Automation Science Engineering, 2013, 10(2): 457-461.

LIU F. Decentralized predictability of discrete event systems[C]// 2017 29th Chinese Control and Decision Conference. Chongqing: Control and Decision, 2017: 2914-2919.

LIU F, YANG P. Verification for the predictability of decentralized discrete event systems with a polynomial complexity[C]// 2017 36th Chinese Control Conference. Dalian: Technical Committee on Control Theory, 2017: 2367-2372.

CASSANDRAS C G, LAFORTUNE S. Introduction to discrete event systems[M]. New York: Springer, 2008.

THORSLEY D, TENEKETZIS D. Diagnosability of stochastic discrete-event systems [J]. IEEE Transactions on Automatic Control, 2005, 50(4): 476-492.

LIU F, QIU D, XING H, et al . Decentralized diagnosis of stochastic discrete event systems [J ] . IEEE Transactions on Automatic Control, 2008, 53(2): 535-546.

LIU F, QIU D. Safe diagnosability of stochastic discrete event systems [J]. IEEE Transactions on Automatic Control, 2008, 53(5): 1291-1296.

CHANG M, DONG W, JI Y D, et al . State estimation based fault prediction for stochastic automatons [J ] . Journal of Tsinghua University (Science and Technology), 2013, 53(11): 1623-1628.

CHEN J, KUMAR R. Stochastic failure prognosability of discrete event systems [J]. IEEE Transactions on Automatic Control, 2015, 60(6): 1570-1581.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Weak Diagnosability of Fuzzy Discrete Event Systems

A Pattern-Based Failure Diagnosis of Fuzzy Discrete-Event Systems

An Optimal Operation Strategy for Community Microgrid Alliances Considering Power Exchange under Multi-package Shared Energy Storage Model

Efficient Temporal Modeling for RGB-T Tracking

Research on Foreign Object Detection in Power Transmission Lines Based on the AAGV-YOLOX Model

Related Author

Zhu Hongzhen

Liu Fuchun

Chen Pinghua

Lun Hao-huai

Liu Fu-chun

Shi Cong-cong

Liu Fu-chun

Related Institution

School of Computer Science and Technology, Guangdong University of Technology

AI问答

⁰