Neural Network Approach to Railway Stand Lateral Skew Control

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F14%3A00226709" target="_blank" >RIV/68407700:21220/14:00226709 - isvavai.cz</a>
Result on the web
<a href="http://airccj.org/CSCP/vol4/csit41928.pdf" target="_blank" >http://airccj.org/CSCP/vol4/csit41928.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5121/csit.2014.4228" target="_blank" >10.5121/csit.2014.4228</a>

Result language
angličtina
Original language name
Neural Network Approach to Railway Stand Lateral Skew Control
Original language description
The paper presents a study of an adaptive approach to lateral skew control for an experimental railway stand. The preliminary experiments with the real experimental railway stand and simulations with its 3-D mechanical model, indicates difficulties of model-based control of the device. Thus, use of neural networks for identification and control of lateral skew shall be investigated. This paper focuses on real-data based modelling of the railway stand by various neural network models, i.e; linear neuralunit and quadratic neural unit architectures. Furthermore, training methods of these neural architectures as such, real-time-recurrent-learning and a variation of back-propagation-through-time are examined, accompanied by a discussion of the produced experimental results.
Czech name
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Czech description
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Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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