| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0450942 |
| utime |
20240103211239.2 |
| mtime |
20160314235959.9 |
| SCOPUS |
84959052132 |
| WOS |
000368103000010 |
| DOI |
10.1088/1742-6596/659/1/012010 |
| title
(primary) (eng) |
On-line Model Structure Selection for Estimation of Plasma Boundary in a Tokamak |
| specification |
| page_count |
10 s. |
| media_type |
E |
|
| serial |
| ARLID |
cav_un_epca*0452609 |
| ISSN |
1742-6588 |
| title
|
Journal of Physics: Conference Series |
| publisher |
| place |
Bristol |
| name |
Institute of Physics Publishing Ltd |
| year |
2015 |
|
|
| keyword |
model structure estimation |
| keyword |
tokamak |
| keyword |
plasma boundary |
| author
(primary) |
| ARLID |
cav_un_auth*0322774 |
| full_dept (cz) |
Adaptivní systémy |
| full_dept (eng) |
Department of Adaptive Systems |
| department (cz) |
AS |
| department (eng) |
AS |
| full_dept |
Department of Adaptive Systems |
| name1 |
Škvára |
| name2 |
Vít |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101207 |
| full_dept (cz) |
Adaptivní systémy |
| full_dept |
Department of Adaptive Systems |
| department (cz) |
AS |
| department |
AS |
| full_dept |
Department of Adaptive Systems |
| name1 |
Šmídl |
| name2 |
Václav |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0107889 |
| full_dept (cz) |
Tokamak |
| full_dept |
Tokamak |
| department (cz) |
TOK |
| department |
TOK |
| full_dept |
Tokamak |
| name1 |
Urban |
| name2 |
Jakub |
| institution |
UFP-V |
| fullinstit |
Ústav fyziky plazmatu AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| abstract
(eng) |
Control of the plasma field in the tokamak requires reliable estimation of the plasma boundary. The plasma boundary is given by a complex mathematical model and the only available measurements are responses of induction coils around the plasma. For the purpose of boundary estimation the model can be reduced to simple linear regression with potentially infinitely many elements. The number of elements must be selected manually and this choice significantly influences the resulting shape. In this paper, we investigate the use of formal model structure estimation techniques for the problem. Specifically, we formulate a sparse least squares estimator using the automatic relevance principle. The resulting algorithm is a repetitive evaluation of the least squares problem which could be computed in real time. Performance of the resulting algorithm is illustrated on simulated data and evaluated with respect to a more detailed and computationally costly model FREEBIE. |
| action |
| ARLID |
cav_un_auth*0322775 |
| name |
12th European Workshop on Advanced Control and Diagnosis (ACD 2015) |
| dates |
19.11.2015 |
| place |
Pilsen |
| country |
CZ |
|
| RIV |
BC |
| reportyear |
2016 |
| inst_support |
RVO:67985556 |
| inst_support |
RVO:61389021 |
| permalink |
http://hdl.handle.net/11104/0252659 |
| mrcbC61 |
1 |
| confidential |
S |
| mrcbT16-s |
0.245 |
| mrcbT16-4 |
Q3 |
| mrcbT16-E |
Q4 |
| arlyear |
2015 |
| mrcbU14 |
84959052132 SCOPUS |
| mrcbU34 |
000368103000010 WOS |
| mrcbU63 |
cav_un_epca*0452609 Journal of Physics: Conference Series 1742-6588 Č. 012010 Bristol Institute of Physics Publishing Ltd 2015 |
|