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Nonlinear modeling of laboratory model AMIRA DR300 by feedforward neural network

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Title: Nonlinear modeling of laboratory model AMIRA DR300 by feedforward neural network
Author: Hubáček, Jiří; Bobál, Vladimír
Document type: Conference paper (English)
Source document: MENDEL 2011. 2011, vol. 2011, p. 191-198
ISSN: 1803-3814 (Sherpa/RoMEO, JCR)
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ISBN: 978-80-214-4302-0
Abstract: Purpose of this paper is to design a nonlinear feedforward neural network model of a laboratory model AMIRA DR300 (made by AMIRA, Duisburg, Germany). This device consists of two direct-current engines, whose shafts are connected together by a fixed shaft coupling. An output value of the laboratory model is a rotation speed of this shaft coupling and it can be measured either by a tachometer generator, or an incremental position sensor. The first engine was modeling by neural network. The second one is used to apply as a generator of a faulty measured value.
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ČSN ISO 690:2011 citation

Citace článku v konferenčním sborníku:
HUBÁČEK, Jiří a Vladimír BOBÁL. Nonlinear modeling of laboratory model AMIRA DR300 by feedforward neural network. In: MENDEL 2011 [online]. Brno: Vysoké učení technické v Brně, 2011, s. 191-198. ISSN 1803-3814.

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