A novel time-delay fuzzy distribution estimation and expression method between the process variables

The time delay between industrial process variables has dynamic characteristics. However, it is quite difficult to estimate and express these dynamic characteristics through traditional methods. In order to deal with this problem, a novel time-delay fuzzy distribution estimation and expression metho...

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Bibliographic Details
Published in2021 IEEE 5th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) pp. 58 - 63
Main Authors Gu, Wen, Lu, Zongrui, Wang, Dan, Jiang, Congbin, Yang, Lifeng, Ding, Xingqiang, Yang, Bo
Format Conference Proceeding
LanguageEnglish
Published IEEE 12.03.2021
Subjects
Delay effects
Estimation
fuzzy time delay distribution
fuzzy timed petri net
Knowledge engineering
knowledge representation
Petri nets
Process control
sliding window
Statistical analysis
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Summary:The time delay between industrial process variables has dynamic characteristics. However, it is quite difficult to estimate and express these dynamic characteristics through traditional methods. In order to deal with this problem, a novel time-delay fuzzy distribution estimation and expression method is presented in this paper. The novel method cuts the target sequence by sliding time window to obtain the target subsequence, then a subsequence that matches the target subsequence by similar calculating in the search sequence can be got, and finally the time-delay sequence information between the two sequences is determined. The fuzzy distribution of the time-delay sequence is calculated by statistical analysis. Then, the improved Data-Driven Fuzzy Time Petri nets (ID-FPNs) are used to describe and express the process information with fuzzy distribution intuitively and effectively. At last, the effectiveness of the method proposed in this paper is validated through a case study.
ISSN:2689-6621
DOI:10.1109/IAEAC50856.2021.9391026