Abnormal Source Identification for Parabolic Distributed Parameter Systems
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Article number | 8936866 |
| Pages (from-to) | 5698-5707 |
| Journal / Publication | IEEE Transactions on Systems, Man, and Cybernetics: Systems |
| Volume | 51 |
| Issue number | 9 |
| Online published | 19 Dec 2019 |
| Publication status | Published - Sep 2021 |
Link(s)
Abstract
Identification of abnormal source hidden in
distributed parameter systems (DPSs) belongs to the category
of inverse source problems. It is important in industrial applications but seldom studied. In this article, we make the first attempt
to investigate the abnormal spatio-temporal (S-T) source identification for a class of DPSs. An inverse S-T model for abnormal
source identification is developed for the first time. It consists
of an adaptive state observer for source identification and an
adaptive source estimation algorithm. One major advantage of
the proposed inverse S-T model is that only the system output
is utilized, without any state measurement. Theoretic analysis is
conducted to guarantee the convergence of the estimation error.
Finally, the performance of the proposed method is evaluated on
a heat transfer rod with an abnormal S-T source.
Research Area(s)
- Adaptive observer, distributed parameter systems (DPSs), inverse source problems
Citation Format(s)
Abnormal Source Identification for Parabolic Distributed Parameter Systems. / Feng, Yun; Li, Han-Xiong; Yang, Hai-Dong.
In: IEEE Transactions on Systems, Man, and Cybernetics: Systems, Vol. 51, No. 9, 8936866, 09.2021, p. 5698-5707.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
