Control Quality Analysis in Accordance with Parametrization in MPC Automation System
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17450%2F22%3AA2302FI3" target="_blank" >RIV/61988987:17450/22:A2302FI3 - isvavai.cz</a>
Výsledek na webu
<a href="https://link.springer.com/chapter/10.1007/978-3-030-97196-0_33" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-97196-0_33</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-97196-0_33" target="_blank" >10.1007/978-3-030-97196-0_33</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Control Quality Analysis in Accordance with Parametrization in MPC Automation System
Popis výsledku v původním jazyce
In automation systems, a parametrization of a controller in a part of its synthesis has an important influence on an accordance to an improving the control quality aspects and on a decreasing the computational complexity. In the field of the process control, as one of the modern control methods, the Model Predictive Control (MPC) has been considered. The MPC strategy is one of a novel and modern approach. In the MPC, the control process has been influenced by parameters dependent on the strategy of the receding horizons. These horizons can be set by programmers of the controller. However, the parametrization has not been so widely bound on the statistical analysis of the MPC progresses of the control quality criterions yet. The quantitative research techniques can be one of the appropriate approaches of decision, which parameters are suitable. In this paper, the statistical methods of the testing differences between the MPC control criterions are proposed as an extended method with regards to the guarantee of a statistical significance. Particularly, the testing differences of the criterions of the MPC automation system is demonstrated on the control of the multivariable model of the process including a consideration of the parametrical (ANOVA) or non-parametrical (Kruskal-Wallis) statistical approaches based on the significance level 0.001.
Název v anglickém jazyce
Control Quality Analysis in Accordance with Parametrization in MPC Automation System
Popis výsledku anglicky
In automation systems, a parametrization of a controller in a part of its synthesis has an important influence on an accordance to an improving the control quality aspects and on a decreasing the computational complexity. In the field of the process control, as one of the modern control methods, the Model Predictive Control (MPC) has been considered. The MPC strategy is one of a novel and modern approach. In the MPC, the control process has been influenced by parameters dependent on the strategy of the receding horizons. These horizons can be set by programmers of the controller. However, the parametrization has not been so widely bound on the statistical analysis of the MPC progresses of the control quality criterions yet. The quantitative research techniques can be one of the appropriate approaches of decision, which parameters are suitable. In this paper, the statistical methods of the testing differences between the MPC control criterions are proposed as an extended method with regards to the guarantee of a statistical significance. Particularly, the testing differences of the criterions of the MPC automation system is demonstrated on the control of the multivariable model of the process including a consideration of the parametrical (ANOVA) or non-parametrical (Kruskal-Wallis) statistical approaches based on the significance level 0.001.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10102 - Applied mathematics
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Proceedings of the International Conference on Intelligent Vision and Computing (ICIVC 2021), Proceedings in Adaptation, Learning and Optimization (vol. 15)
ISBN
978-3-030-97196-0
ISSN
2363-6084
e-ISSN
2363-6092
Počet stran výsledku
10
Strana od-do
403-412
Název nakladatele
Springer
Místo vydání
Cham
Místo konání akce
online
Datum konání akce
3. 10. 2021
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
—