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A new prediction algorithm to improve training the neural networks and its application in mobile robot control system
Electrical and Computer and Biomedical Engineering Department, Islamic Azad University.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
2011 (English)In: 2011 9th IEEE International Conference on Control and Automation (ICCA 2011): Santiago, Chile, 19 - 21 December 2011, Piscataway, NJ: IEEE Communications Society, 2011, p. 429-433Conference paper, Published paper (Refereed)
Abstract [en]

This paper proposes a new prediction model for stable control of mobile robot based on chaotic neural networks. Programming mobile robots can be long and difficult task. In this study, we intend to demonstrate the chaotic learning algorithm to improve neural networks' learning efficiency and obtain better prediction. In order to validate the prediction performance of recurrent neural networks, a novel stimulation study and analysis paradigm has been done on the practical data. Finally, through computer simulations, we demonstrate the effectiveness and stability of the proposed controller according to changed working conditions

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Communications Society, 2011. p. 429-433
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-27559DOI: 10.1109/ICCA.2011.6137939Scopus ID: 2-s2.0-84858952376Local ID: 10e363cd-c606-4cc7-a41a-bcd4f6b501b5ISBN: 978-1-457-71475-7 (print)OAI: oai:DiVA.org:ltu-27559DiVA, id: diva2:1000743
Conference
IEEE International Conference on Control & Automation : 19/12/2011 - 21/12/2011
Note
Godkänd; 2012; 20120404 (andbra)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-07-10Bibliographically approved

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Fakharian, Ahmad

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
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  • Other style
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Language
  • de-DE
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  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • asciidoc
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