1 Ocak 2017 Dergi makalesi Açık Erişim

Atlihan, Murat; Yalcin, Baris Can; Erkan, Kadir

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/47177</identifier>
  <creators>
    <creator>
      <creatorName>Atlihan, Murat</creatorName>
      <givenName>Murat</givenName>
      <familyName>Atlihan</familyName>
      <affiliation>Yildiz Tech Univ, Dept Mech Engn, Fac Mech Engn, Istanbul, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Yalcin, Baris Can</creatorName>
      <givenName>Baris Can</givenName>
      <familyName>Yalcin</familyName>
      <affiliation>Yildiz Tech Univ, Dept Mech Engn, Fac Mech Engn, Istanbul, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Erkan, Kadir</creatorName>
      <givenName>Kadir</givenName>
      <familyName>Erkan</familyName>
      <affiliation>Yildiz Tech Univ, Dept Mech Engn, Fac Mech Engn, Istanbul, Turkey</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Force And Torque Parameter Estimation For A 4-Pole Hybrid Electromagnet By Anfis Hybrid Learning Algorithm</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2017</publicationYear>
  <dates>
    <date dateType="Issued">2017-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/47177</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.3906/elk-1605-364</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">In this study, a force and torque estimation method based on an adaptive neuro-fuzzy inference system (ANFIS) has been developed to get rid of multiple integral calculations of air gap coefficients that cause time delay for magnetic levitation control applications. During magnetic levitation applications that contain a 4-pole hybrid electromagnet, multiple integral calculations have to be done for obtaining air gap permanence parameters, and these parameters are needed to calculate force and torque parameters that are produced by the poles of the hybrid electromagnet, which means, if time delay occurs for calculation of permanence parameters, actual force and actual torque values that are produced by hybrid electromagnet's poles cannot be exactly known; thus, the advantage of having an exact model of the system gets lost and, as a result, the controller's performance goes down. To address a solution, an ANFIS using a hybrid learning algorithm consisting of backpropagation and least-squares learning methods is proposed to estimate force and torque parameters using training data already obtained using multiple integral calculations before.</description>
  </descriptions>
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