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[citace_text] => ŠEDA, M. Fuzzy Shortest Paths Approximation for Solving the Fuzzy Steiner Tree Problem in Graphs. Transactions on Engineering, Computing and Technology, 2006, vol. 14, no. 8, 5 p. ISSN: 1305-5313.
[citace_html] => ŠEDA, M. Fuzzy Shortest Paths Approximation for Solving the Fuzzy Steiner Tree Problem in Graphs. Transactions on Engineering, Computing and Technology, 2006, vol. 14, no. 8, 5 p. ISSN: 1305-5313.
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journal="Transactions on Engineering, Computing and Technology",
year="2006",
volume="14",
number="8",
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issn="1305-5313"
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[nazev_en] => Fuzzy Shortest Paths Approximation for Solving the Fuzzy Steiner Tree Problem in Graphs
[popis_en] => In this paper, we deal with the Steiner tree problem (STP) on a graph in which a fuzzy number, instead of a real number, is assigned to each edge. We propose a modification of the shortest paths approximation based on the fuzzy shortest paths (FSP) evaluations. Since a fuzzy min operation using the extension principle leads to nondominated solutions, we propose another approach to solving the FSP using Cheng's centroid point fuzzy ranking method.
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[citace_text] => DAVIDOVÁ, O. Ukazatele kvality regulace při návrhu diskrétního regulačního obvodu. Automa, 2006, roč. 12, č. 10, 4 s. ISSN: 1210-9592.
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journal="Automa",
year="2006",
volume="12",
number="10",
pages="4",
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[popis] => Při syntéze diskrétního regulačního obvodu se mnoho metod. Některé z nich jsou využívány k určení klasického číslicového regulátor, jiné k návrhu obecného číslicového regulátoru, označovaného též jako číslicový korekční člen. V článku jsou vybrané metody syntézy porovnány s metodou typizované logaritmické amplitudové frekvenční charakteristiky v její variantě pro diskrétní regulační obvody.
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journal="Automa",
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volume="12",
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issn="1210-9592"
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[nazev_en] => Compare of discrete control circuit synthesis methods
[popis_en] => A lot of methods are used for the discrete control circuit design. Some of methods are used for classical digital controller settings, other for universal digital controller referred to as digital correcting element. The paper compared selected synthesis methods with method of standardized logarithmic amplitude frequency characteristic in discrete control circuit alternate.
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[nazev_orig] => Self-learning controller of active magnetic bearing based on CARLA method
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[popis] => The active magnetic bearing control through analytically designed linear PD regulator, with parallel nonlinear compensation represented by automatic approximator is described in this contribution. Coefficient (parameter) values come from actions of Continuous Action Reinformcement Learning Automata (CARLAs). Influence of CARLAs parameters to learning is discussed. Parameters influence is proved by simulation study. It is shown that learning improvement can be reached by selecting appropriate parameters of learning.
[popis_orig] => The active magnetic bearing control through analytically designed linear PD regulator, with parallel nonlinear compensation represented by automatic approximator is described in this contribution. Coefficient (parameter) values come from actions of Continuous Action Reinformcement Learning Automata (CARLAs). Influence of CARLAs parameters to learning is discussed. Parameters influence is proved by simulation study. It is shown that learning improvement can be reached by selecting appropriate parameters of learning.
[klicova_slova] => control, active magnetic bearing, reinforcement learning
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[url] =>
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[odpovedny_utvar_nazev] => Institute of Automation and Computer Science
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[citace_text] => BŘEZINA, T.; TUREK, M.; PULCHART, J. Self-learning controller of active magnetic bearing based on CARLA method. Pomiary Automatyka Kontrola, 2007, vol. 2007, no. 1, p. 6-9. ISSN: 0032-4140.
[citace_html] => BŘEZINA, T.; TUREK, M.; PULCHART, J. Self-learning controller of active magnetic bearing based on CARLA method. Pomiary Automatyka Kontrola, 2007, vol. 2007, no. 1, p. 6-9. ISSN: 0032-4140.
[citace_rtf] =>
[citace_bibtex] => @article{BUT44001,
author="Tomáš {Březina} and Milan {Turek} and Jaroslav {Pulchart}",
title="Self-learning controller of active magnetic bearing based on CARLA method",
journal="Pomiary Automatyka Kontrola",
year="2007",
volume="2007",
number="1",
pages="6--9",
issn="0032-4140"
}
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[nazev_en] => Self-learning controller of active magnetic bearing based on CARLA method
[popis_en] => The active magnetic bearing control through analytically designed linear PD regulator, with parallel nonlinear compensation represented by automatic approximator is described in this contribution. Coefficient (parameter) values come from actions of Continuous Action Reinformcement Learning Automata (CARLAs). Influence of CARLAs parameters to learning is discussed. Parameters influence is proved by simulation study. It is shown that learning improvement can be reached by selecting appropriate parameters of learning.
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