| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0477603 |
| utime |
20240103214445.7 |
| mtime |
20170906235959.9 |
| SCOPUS |
85035352997 |
| WOS |
000425229300125 |
| DOI |
10.1109/MMAR.2017.8046912 |
| title
(primary) (eng) |
Online Tuned Model Predictive Control for Robotic Systems with Bounded Noise |
| specification |
| page_count |
6 s. |
| media_type |
C |
|
| serial |
| ARLID |
cav_un_epca*0477597 |
| ISBN |
978-1-5386-2403-6 |
| title
|
Proceedings of the 22nd IEEE International Conference on Methods and Models in Automation and Robotics |
| page_num |
694-699 |
| publisher |
| place |
Szczecin |
| name |
West Pomeranian University of Technology |
| year |
2017 |
|
|
| keyword |
Model predictive control |
| keyword |
Bounded noise |
| keyword |
State estimation |
| keyword |
Noise parameter estimation |
| keyword |
linear programming |
| author
(primary) |
| ARLID |
cav_un_auth*0101064 |
| full_dept (cz) |
Adaptivní systémy |
| full_dept (eng) |
Department of Adaptive Systems |
| department (cz) |
AS |
| department (eng) |
AS |
| full_dept |
Department of Adaptive Systems |
| share |
50 |
| name1 |
Belda |
| name2 |
Květoslav |
| 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 |
| share |
50 |
| name1 |
Pavelková |
| name2 |
Lenka |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| abstract
(eng) |
This paper deals with a discrete predictive control design for motion control of robotic systems. The design considers time-varying state-space robot model. It is assumed that used robot state has to be estimated from measured robot outputs. These outputs represent controlled quantities including a bounded noise. Considering this arrangement, the paper introduces a novel solution to the state and noise parameter estimations based on linear programming that is incorporated in the control design. Estimated states are utilised for updating state-dependent elements in the robot model and for control design itself. Estimated noise parameters are employed in advanced tuning of control parameters, namely penalisation matrices. The proposed theoretical outcomes are demonstrated on one multi-input multi-output robot-manipulator as a specific representative of robotic systems. |
| action |
| ARLID |
cav_un_auth*0349323 |
| name |
22nd IEEE International Conference on Methods and Models in Automation and Robotics |
| dates |
20170828 |
| mrcbC20-s |
20170831 |
| place |
Miedzyzdroje |
| country |
PL |
|
| RIV |
BC |
| FORD0 |
20000 |
| FORD1 |
20200 |
| FORD2 |
20205 |
| reportyear |
2018 |
| num_of_auth |
2 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0274233 |
| confidential |
S |
| mrcbC86 |
n.a. Proceedings Paper Automation Control Systems|Robotics |
| arlyear |
2017 |
| mrcbU14 |
85035352997 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000425229300125 WOS |
| mrcbU63 |
cav_un_epca*0477597 Proceedings of the 22nd IEEE International Conference on Methods and Models in Automation and Robotics 978-1-5386-2403-6 694 699 Szczecin West Pomeranian University of Technology 2017 |
|