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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%2F61988987%3A17450%2F22%3AA2302FI3" target="_blank" >RIV/61988987:17450/22:A2302FI3 - isvavai.cz</a>

  • Result on the web

    <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>

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, 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.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10102 - Applied mathematics

Result continuities

  • Project

  • 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), Proceedings in Adaptation, Learning and Optimization (vol. 15)

  • ISBN

    978-3-030-97196-0

  • ISSN

    2363-6084

  • e-ISSN

    2363-6092

  • Number of pages

    10

  • Pages from-to

    403-412

  • Publisher name

    Springer

  • Place of publication

    Cham

  • Event location

    online

  • Event date

    Oct 3, 2021

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article