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  <titleInfo>
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    <title>stator resistance estimation of induction motor using neural network</title>
  </titleInfo>
  <titleInfo type="alternative">
    <title>A stator resistance estimation of induction motor using neural network</title>
  </titleInfo>
  <name type="personal">
    <namePart>Mohd Shukri Alias</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <typeOfResource>text</typeOfResource>
  <genre authority="marc">theses</genre>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">my</placeTerm>
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    <place>
      <placeTerm type="text">Kuantan, Pahang</placeTerm>
    </place>
    <publisher>UMP</publisher>
    <dateIssued>2010</dateIssued>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
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    <extent>xv, 51 p. : ill. (some col.) ; 30 cm. + 1 computer disc</extent>
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  <abstract>During the operation of induction motor, stator resistance changes incessantly with the temperature of the working machine. This situation may cause an error in rotor resistance estimation of the same magnitude and will produce an error between the actual and estimated motor torque which can leads to motor breakdown in worst cases. Therefore, this project will propose an approach to estimate stator resistance of induction motor using neural network. Then, a correction will be made to ensure the stabilization of the system.This work has been motivated by the recent use of neural networks in different industry applications, and by their several advantages over the conventional controllers, such as stability, reliability, speed, and robustness.</abstract>
  <targetAudience authority="marctarget">specialized</targetAudience>
  <note type="statement of responsibility">Mohd Shukri Alias</note>
  <note>Project paper (Bachelor of Electrical Engineering (Electronics)) -- Universiti Malaysia Pahang - 2010</note>
  <note>Bibliography : p. 43-44</note>
  <subject authority="lcsh">
    <topic>Electric driving</topic>
    <topic>Automatic control</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Electric motors</topic>
    <topic>Automatic control</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Neural networks (Computer science)</topic>
  </subject>
  <identifier type="isbn">THE0006823(Local)</identifier>
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    <recordCreationDate encoding="marc">110722</recordCreationDate>
    <recordChangeDate encoding="iso8601">20251114204502.0</recordChangeDate>
    <recordIdentifier source="KUKTEM">vtls000055045</recordIdentifier>
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