Techniques for predictor design in multivariable predictive control

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F11%3A43865603" target="_blank" >RIV/70883521:28140/11:43865603 - isvavai.cz</a>
Alternative codes found
RIV/70883521:28610/11:43865603
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Techniques for predictor design in multivariable predictive control
Original language description
Model Based Predictive Control (MBPC) or only Predictive Control is one of the control methods which have developed considerably over a few past years. It is mostly based on discrete models of controlled systems. Model of a controlled system is used forcomputation of predictions of the systems output on the basis of past inputs, outputs and states and designed sequence of future control increments. This paper is focused in comparison of various approaches to computation of multi-step-ahead predictionsusing a multivariable input - output model. Computational aspects of derivation of predictions can be limiting especially in adaptive predictive control. Many processes are affected by external disturbances that can be measured. Inclusion of measurable disturbances into prediction equations for different approaches was also elaborated.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BC - Theory and management systems
OECD FORD branch
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Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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