Name
Title | ||
|---|---|---|
Abnormal spatio‐temporal source estimation for a linear unstable parabolic distributed parameter system: An adaptive PDE observer perspective |
Abstract | ||
|---|---|---|
Detection and estimation of abnormalities for distributed parameter system (DPS) have wide applications in industry, e.g., battery thermal fault diagnosis, quality monitoring of hot-rolled strip laminar cooling process. In this paper, the abnormal spatio-temporal (S-T) source detection and estimation problem for a linear unstable DPS is first studied. The proposed methodology consists of two steps: first, an abnormality detection filter (ADF) which generates a residual signal for abnormality detection in the time domain is constructed using pointwise measurement; Then, an adaptive Luenberger-type PDE observer including an adaptive estimation algorithm is designed and triggered only when an alarm raises from the ADF. Theoretic analysis based on the spatial domain decomposition approach is presented to show the convergence of the estimation errors. Finally, an illustrative example is presented to show the performance of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.jfranklin.2020.12.006 | Journal of the Franklin Institute |
DocType | Volume | Issue |
Journal | 358 | 2 |
ISSN | Citations | PageRank |
0016-0032 | 1 | 0.35 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yun Feng | 1 | 1 | 1.36 |
| Yaonan Wang | 2 | 1150 | 118.92 |
| Jun-Wei Wang | 3 | 9 | 1.78 |
| Hanxiong Li | 4 | 2519 | 157.48 |