吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (01): 123-129.

Previous Articles     Next Articles

Codiagnosability verification of discrete event systems

LI Zhan-shan1, JIN Zhi-min1,2, YANG Feng-jie2, XU Pei-zhi2   

  1. 1. Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China;
    2. College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Received:2012-02-27 Online:2013-01-01 Published:2013-01-01

RICH HTML

0   

PDF (PC)

312

Abstract: A polynomial algorithm of codiagnosability verification of discrete event systems was proposed, which can be used to verify F-codiagnosability and NF-codiagnosability of system respectively. Algorithm is achieved by constructing a test automaton which extracts the fault path and the normal path to compare. In addition, the traditional codiagnosability was divided into two case, it can improve the efficiency of the algorithm. Both complexity analysis and case study have shown that our algorithm has more lower computational complexity. The experimental results verify the effectiveness and efficiency of the method.

Key words: artificial intelligence, model-based diagnosis, discrete-event system, verification algorithm, F-codiagnosability, NF-codiagnosability

CLC Number: 

  • TP18
[1] 赵相福. 离散事件系统基于模型诊断的若干问题研究.长春:吉林大学计算机科学与技术学院, 2009. Zhao Xiang-fu. Research on some problems about model-based diagnosis of discrete dvent systems. Changchun: College of Computer Science and Technology, Jilin University, 2009.

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

[3] Jiang S, Huang Z, Chandra V, et al. A polynomial algorithm for testing diagnosability of discrete-event systems[J]. IEEE Transactions on Automatic Control, 2001, 46(8): 1318-1321.

[4] Yoo T S, Lafortune S. Polynomial-time verication of diagnosability of partially observed discrete-event systems[J]. IEEE Transactions on Automatic Control, 2002, 47(9): 1491-1495.

[5] Debouk R, Lafortune S, Teneketzis D. Coordinated decentralized protocols for failure diagnosis of discrete event systems[J]. Discrete Event Dynamic Systems: Theory and Applications, 2000, 10(1): 33-86.

[6] 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.

[7] Wang Y, Yoo T S, Lafortune S. Diagnosis of discrete event systems using decentralized architectures[J]. Discrete Event Dynamic Systems, 2007, 17: 233-263.

[8] Basilio J C, Lafortune S. Robust codiagnosability of discrete event systems//Proceeding of American Control Conference, St. Louis, MO, 2009: 2202-2209.

[9] Moreira Marcos V, Jesus Thiago C, Basilio Joo C. Polynomial time verification of decentralized diagnosability of discrete event systems[J]. IEEE Transactions on Automatic Control, 2011, 56(7): 1679-1684.

[10] Wang Y, Lafortune S, Yoo T S. Decentralized diagnosis of discrete event systems using unconditional and conditional decisions//Proceedings of the 44th IEEE Conference on Decision and Control, 2005: 6298-6304.
[1] DONG Sa, LIU Da-you, OUYANG Ruo-chuan, ZHU Yun-gang, LI Li-na. Logistic regression classification in networked data with heterophily based on second-order Markov assumption [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1571-1577.
[2] GU Hai-jun, TIAN Ya-qian, CUI Ying. Intelligent interactive agent for home service [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1578-1585.
[3] WANG Xu, OUYANG Ji-hong, CHEN Gui-fen. Measurement of graph similarity based on vertical dimension sequence dynamic time warping method [J]. 吉林大学学报(工学版), 2018, 48(4): 1199-1205.
[4] ZHANG Hao, ZHAN Meng-ping, GUO Liu-xiang, LI Zhi, LIU Yuan-ning, ZHANG Chun-he, CHANG Hao-wu, WANG Zhi-qiang. Human exogenous plant miRNA cross-kingdom regulatory modeling based on high-throughout data [J]. 吉林大学学报(工学版), 2018, 48(4): 1206-1213.
[5] HUANG Lan, JI Lin-ying, YAO Gang, ZHAI Rui-feng, BAI Tian. Construction of disease-symptom semantic net for misdiagnosis prompt [J]. 吉林大学学报(工学版), 2018, 48(3): 859-865.
[6] LI Xiong-fei, FENG Ting-ting, LUO Shi, ZHANG Xiao-li. Automatic music composition algorithm based on recurrent neural network [J]. 吉林大学学报(工学版), 2018, 48(3): 866-873.
[7] LIU Jie, ZHANG Ping, GAO Wan-fu. Feature selection method based on conditional relevance [J]. 吉林大学学报(工学版), 2018, 48(3): 874-881.
[8] WANG Xu, OUYANG Ji-hong, CHEN Gui-fen. Heuristic algorithm of all common subsequences of multiple sequences for measuring multiple graphs similarity [J]. 吉林大学学报(工学版), 2018, 48(2): 526-532.
[9] YANG Xin, XIA Si-jun, LIU Dong-xue, FEI Shu-min, HU Yin-ji. Target tracking based on improved accelerated gradient under tracking-learning-detection framework [J]. 吉林大学学报(工学版), 2018, 48(2): 533-538.
[10] LIU Xue-juan, YUAN Jia-bin, XU Juan, DUAN Bo-jia. Quantum k-means algorithm [J]. 吉林大学学报(工学版), 2018, 48(2): 539-544.
[11] QU Hui-yan, ZHAO Wei, QIN Ai-hong. A fast collision detection algorithm based on optimization operator [J]. 吉林大学学报(工学版), 2017, 47(5): 1598-1603.
[12] LI Jia-fei, SUN Xiao-yu. Clustering method for uncertain data based on spectral decomposition [J]. 吉林大学学报(工学版), 2017, 47(5): 1604-1611.
[13] SHAO Ke-yong, CHEN Feng, WANG Ting-ting, WANG Ji-chi, ZHOU Li-peng. Full state based adaptive control of fractional order chaotic system without equilibrium point [J]. 吉林大学学报(工学版), 2017, 47(4): 1225-1230.
[14] WANG Sheng-sheng, WANG Chuang-feng, GU Fang-ming. Spatio-temporal reasoning for OPRA direction relation network [J]. 吉林大学学报(工学版), 2017, 47(4): 1238-1243.
[15] MA Miao, LI Yi-bin. Multi-level image sequences and convolutional neural networks based human action recognition method [J]. 吉林大学学报(工学版), 2017, 47(4): 1244-1252.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd