Robust predictability of stochastic discrete-event systems and a polynomial-time verification

被引:1
|
作者
Liao, Hui [1 ,3 ]
Liu, Fuchun [1 ]
Wu, Naiqi [2 ]
机构
[1] Guangdong Univ Technol, Sch Comp, Guangzhou 510006, Peoples R China
[2] Macau Univ Sci & Technol, Inst Syst Engn, Taipa, Macau, Peoples R China
[3] Foshan Univ, Sch Math & Big Data, Foshan 528000, Peoples R China
基金
中国国家自然科学基金;
关键词
Fault prediction; Robust predictability; Discrete -event systems; Stochastic automata; NONBLOCKING SUPERVISORY CONTROL; DECENTRALIZED DIAGNOSIS; DIAGNOSABILITY;
D O I
10.1016/j.automatica.2022.110477
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The purpose of fault prediction of discrete-event systems (DESs) is to predict the occurrence of fault in advance such that some protective actions can be taken before the occurrence of the fault. The robust predictability issue under the framework of stochastic DESs (SDESs) with model uncertainty is studied. First, the notions of (epsilon, m)-robust predictability and robust predictability of SDESs are formalized. In general, a set of stochastic systems being robustly predictable can predict the occurrences of faults in the sense of probability. Then the robust predictor and robust verifier for performing the robust prediction are constructed from the given possible stochastic systems. Particularly, the necessary and sufficient conditions for (epsilon, m)-robust predictability and robust predictability of SDESs are proposed, and an approach is presented to verify the robust predictability of SDESs with polynomial-time complexity both in the state space and in the number of all possible models. (C) 2022 Elsevier Ltd. All rights reserved.
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页数:9
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