Convenient Optimization Strategy Implemented in Multivariable Predictive Control

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17450%2F18%3AA1901UVQ" target="_blank" >RIV/61988987:17450/18:A1901UVQ - isvavai.cz</a>
Alternative codes found
RIV/70883521:28140/18:63519939
Result on the web
<a href="https://www.matec-conferences.org/articles/matecconf/abs/2018/69/matecconf_cscc2018_02022/matecconf_cscc2018_02022.html" target="_blank" >https://www.matec-conferences.org/articles/matecconf/abs/2018/69/matecconf_cscc2018_02022/matecconf_cscc2018_02022.html</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1051/matecconf/201821002022" target="_blank" >10.1051/matecconf/201821002022</a>

Result language
angličtina
Original language name
Convenient Optimization Strategy Implemented in Multivariable Predictive Control
Original language description
A significantly important part of model predictive control (MPC) with constraints is a solution of an optimization task. The result of the optimization is a vector of future increments of a manipulated variable. The first element of this vector is applied in the next sampling period of MPC in the framework of a receding horizon strategy. In practical realization of a multivariable MPC, the optimization is characterized by higher computational complexity. Therefore, reduction of the computational complexity of the optimization methods has been widely researched. One suitable principle of precomputing operations was proposed by Wang, L. This general optimization strategy is further modified in this paper. Decreasing of the computational complexity of the optimization by using of the proposed modification is discussed.
Czech name
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Czech description
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Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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