| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0536061 |
| utime |
20250123090100.8 |
| mtime |
20201214235959.9 |
| SCOPUS |
85098241378 |
| WOS |
000635651400155 |
| DOI |
10.1109/CoDIT49905.2020.9263867 |
| title
(primary) (eng) |
Output-Feedback Model Predictive Control for Systems under Uniform Disturbances |
| specification |
| page_count |
6 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0536369 |
| ISBN |
978-1-7281-5954-6 |
| ISSN |
Proceedings of the 7th International Conference on Control, Decision and Information Technologies (CoDIT) 2020 |
| title
|
Proceedings of the 7th International Conference on Control, Decision and Information Technologies (CoDIT) 2020 |
| page_num |
897-902 |
| publisher |
| place |
Piscataway |
| name |
IEEE |
| year |
2020 |
|
|
| keyword |
output-feedback model predictive control |
| keyword |
bounded uncertainty |
| keyword |
Bayesian state estimation |
| keyword |
parallel kinematic machine |
| author
(primary) |
| ARLID |
cav_un_auth*0382598 |
| name1 |
Kuklišová Pavelková |
| name2 |
Lenka |
| institution |
UTIA-B |
| full_dept (cz) |
Adaptivní systémy |
| full_dept (eng) |
Department of Adaptive Systems |
| department (cz) |
AS |
| department (eng) |
AS |
| full_dept |
Department of Adaptive Systems |
| country |
CZ |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101064 |
| name1 |
Belda |
| name2 |
Květoslav |
| institution |
UTIA-B |
| full_dept (cz) |
Adaptivní systémy |
| full_dept |
Department of Adaptive Systems |
| department (cz) |
AS |
| department |
AS |
| full_dept |
Department of Adaptive Systems |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
GA18-15970S |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0362986 |
|
| abstract
(eng) |
The paper deals with an output-feedback model predictive control (MPC) for discrete-time systems influenced by bounded disturbances. The proposed MPC combines a state-space design and a state estimation. The state estimates are obtained by a specific uniform Bayesian filter. It provides an evident disturbance attenuation in the estimated state. The MPC design considers a quadratic cost function that incorporates penalties on the tracking error, on the actuation effort and on the system output increments. The theoretical results are completed by illustrative examples using a dynamic model of a parallel kinematic machine as a controlled system. |
| action |
| ARLID |
cav_un_auth*0400949 |
| name |
International Conference on Control, Decision and Information Technologies 2020 (CoDIT 2020) /7./ |
| dates |
20200629 |
| mrcbC20-s |
20200702 |
| place |
Prague |
| country |
CZ |
|
| RIV |
BC |
| FORD0 |
20000 |
| FORD1 |
20200 |
| FORD2 |
20204 |
| reportyear |
2021 |
| num_of_auth |
2 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0314148 |
| confidential |
S |
| arlyear |
2020 |
| mrcbU14 |
85098241378 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000635651400155 WOS |
| mrcbU63 |
cav_un_epca*0536369 Proceedings of the 7th International Conference on Control, Decision and Information Technologies (CoDIT) 2020 IEEE 2020 Piscataway 897 902 978-1-7281-5954-6 2576-3555 |
|