| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0446091 |
| utime |
20240103210322.9 |
| mtime |
20150806235959.9 |
| SCOPUS |
84943513835 |
| WOS |
000381618600081 |
| title
(primary) (eng) |
Estimation of Uniform Static Regression Model with Abruptly Varying Parameters |
| specification |
| page_count |
5 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0446089 |
| ISBN |
978-989-758-122-9 |
| title
|
Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics |
| part_num |
1 |
| part_title |
Volume 1 |
| page_num |
603-607 |
| publisher |
| place |
Portugal |
| name |
SCITEPRESS – Science and Technology Publications |
| year |
2015 |
|
| editor |
|
| editor |
|
| editor |
|
| editor |
|
|
| keyword |
Sensor Condition |
| keyword |
Abrupt Change |
| keyword |
Signal Variance |
| keyword |
Uniform Distribution |
| author
(primary) |
| ARLID |
cav_un_auth*0101119 |
| 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 |
Jirsa |
| name2 |
Ladislav |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101175 |
| full_dept (cz) |
Adaptivní systémy |
| full_dept |
Department of Adaptive Systems |
| department (cz) |
AS |
| department |
AS |
| full_dept |
Department of Adaptive Systems |
| name1 |
Pavelková |
| name2 |
Lenka |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| ARLID |
cav_un_auth*0291242 |
| project_id |
7D12004 |
| agency |
GA MŠk |
|
| abstract
(eng) |
A modular framework for monitoring complex systems contains blocks that evaluate condition of single signals, typically of sensors. The signals are modelled and their values must be found within the prescribed bounds. However, an abrupt change of the signal ncreases the estimated parameters’ variance, which raises uncertainty of the sensor condition although it operates correctly. This increase affects the whole system in evaluation of condition uncertainty. The solution must be fast and simple, because of runtime application requirements. The signal is modelled by a static model with uniform noise, variance increase is tested and if detected, the model memory is cleared. The fast and efficient algorithm is demonstrated on industrial rolling data. The method prevents the parameters’ variance from the artificial increase. |
| action |
| ARLID |
cav_un_auth*0318350 |
| name |
12th International Conference on Informatics in Control, Automation and Robotics - ICINCO 2015 |
| dates |
21.07.2015-23.07.2015 |
| place |
Colmar |
| country |
FR |
|
| RIV |
BC |
| reportyear |
2016 |
| num_of_auth |
2 |
| presentation_type |
PO |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0248315 |
| confidential |
S |
| arlyear |
2015 |
| mrcbU14 |
84943513835 SCOPUS |
| mrcbU34 |
000381618600081 WOS |
| mrcbU63 |
cav_un_epca*0446089 Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics Volume 1 1 978-989-758-122-9 603 607 Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics Portugal SCITEPRESS – Science and Technology Publications 2015 |
| mrcbU67 |
Filipe J. 340 |
| mrcbU67 |
Madani K. 340 |
| mrcbU67 |
Gusikhin O. 340 |
| mrcbU67 |
Sasiadek J. 340 |
|