| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0459995 |
| utime |
20240103212314.0 |
| mtime |
20160610235959.9 |
| SCOPUS |
84991037566 |
| WOS |
000381504800162 |
| DOI |
10.1016/j.ifacol.2016.07.327 |
| title
(primary) (eng) |
State Estimation and Model Predictive Control for the Systems with Uniform Noise |
| specification |
| page_count |
6 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0472095 |
| ISSN |
2405-8963 |
| title
|
IFAC-PapersOnLine. Volume 49, Issue 7 - 11th IFAC Symposium on Dynamics and Control of Process SystemsIncluding Biosystems DYCOPS-CAB 2016 |
| page_num |
967-972 |
| publisher |
| place |
Trondheim |
| name |
IFAC |
| year |
2016 |
|
|
| keyword |
model predictive control |
| keyword |
bounded noise |
| keyword |
probabilistic models |
| keyword |
linear state-space models |
| author
(primary) |
| ARLID |
cav_un_auth*0101175 |
| 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 |
Pavelková |
| name2 |
Lenka |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101064 |
| full_dept (cz) |
Adaptivní systémy |
| full_dept |
Department of Adaptive Systems |
| department (cz) |
AS |
| department |
AS |
| full_dept |
Department of Adaptive Systems |
| name1 |
Belda |
| name2 |
Květoslav |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| ARLID |
cav_un_auth*0331019 |
| project_id |
GA16-09848S |
| agency |
GA AV ČR |
|
| abstract
(eng) |
This paper concerns the model predictive control applied to the systems with bounded uncertainties. These systems are described by a state-space model with uniformly distributed states and outputs with unknown bounds of respective distributions. The model matrices are assumed to be known. The approximate estimation of states and noise bounds is based on the Bayesian approach. A state-space generalised predictive control is selected as a suitable target model predictive control strategy. The proposed concept of the above mentioned estimation within generalised predictive control is illustrated by representative comparative simulation examples. |
| action |
| ARLID |
cav_un_auth*0331299 |
| name |
IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems (DYCOPS-CAB) /11./ |
| dates |
20160606 |
| mrcbC20-s |
20160608 |
| place |
Trondheim |
| country |
NO |
|
| RIV |
BC |
| reportyear |
2017 |
| num_of_auth |
2 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0260441 |
| confidential |
S |
| mrcbC86 |
n.a. Proceedings Paper Automation Control Systems |
| mrcbT16-s |
0.298 |
| mrcbT16-4 |
Q3 |
| mrcbT16-E |
Q3 |
| arlyear |
2016 |
| mrcbU14 |
84991037566 SCOPUS |
| mrcbU34 |
000381504800162 WOS |
| mrcbU63 |
cav_un_epca*0472095 IFAC-PapersOnLine. Volume 49, Issue 7 - 11th IFAC Symposium on Dynamics and Control of Process SystemsIncluding Biosystems DYCOPS-CAB 2016 2405-8963 967 972 Trondheim IFAC 2016 |
|