Control Quality Analysis in Accordance with Parametrization in MPC Automation System
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F22%3A63557198" target="_blank" >RIV/70883521:28140/22:63557198 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-030-97196-0_33" target="_blank" >http://dx.doi.org/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>
Alternative languages
Result language
angličtina
Original language name
Control Quality Analysis in Accordance with Parametrization in MPC Automation System
Original language description
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, he 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 ontroller. 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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the International Conference on Intelligent Vision and Computing (ICIVC 2021)
ISBN
978-3-030-97195-3
ISSN
2363-6084
e-ISSN
2363-6092
Number of pages
10
Pages from-to
403-412
Publisher name
Springer Nature AG
Place of publication
Basel
Event location
Omán
Event date
Oct 3, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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