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    <title>application of modified adaptive bats sonar algorithm (MABSA) on fuzzy logic controller for dc motor accuracy</title>
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  <name type="personal">
    <namePart>Nurainaa Elas</namePart>
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    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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    <extent>xii, 78 pages : illustrations (some color) ; 30 cm. + 1 CD ROM</extent>
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  <abstract>Controllers  are  mostly  used  to  improve  the  control  system  performance.  The  works  related to controllers attract researchers since the controller can be applied to solve many  industrial  problems  involving  speed  and  position.  Fuzzy  logic  controller  (FLC)  gains  popularity since it is widely used in industrial application. However, the FLC structure is  still lacking in terms of the accuracy and time response. Although there are optimization  technique used to obtain both accuracy and time response, it is still lacking. Therefore,  this research presents works on the FLC system which is the fuzzy inference system that  will be optimized by the modified adaptive bats sonar algorithm (MABSA) for the DC  servo  motor  position  control.  The  MABSA  will  be  optimized  with  the  range  of  the  membership  input  in  the  FLC.  The  research  aims  are  to  achieve  accuracy  while  minimizing the time response of the DC servo motor. This is done by designing the FLC  using  the  Matlab  toolbox.  After  the  FLC  is  designed  completely,  the  Simulink  block  diagram  for  the  DC  servo  motor  and  FLC  are  built  to  see  the  performance  of  the  controller. The range of the membership function for inputs and outputs will be optimized  by the MABSA to get the best positional values. The performance of the developed FLC  with the optimized MABSA is verified through the simulation and robustness tests with  the  system  that  did  not  use  the  FLC  and  also  the  system  without  MABSA.  It  was  demonstrated  from  the  study  that  the  proposed  FLC  with  optimization  of  MABSA  algorithm  was  able  to  yield  an  improvement  of  3.8%  with  respect  to  the  rise  time  in  comparison to other control schemes evaluated. When compared with  PSO algorithm,  proposed FLC optimized by MABSA showed improvement by 12.5% in rise time and  10%  in  settling  time.  PSO-FLC  also  give  0.6%  steady  state  error  compared  to  the  MABSA-FLC. In conclusion, the results validate the better performance in terms of rise  time and settling time of the developed FLC that has been optimized by the MABSA.</abstract>
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  <note type="statement of responsibility">Nurainaa Elas</note>
  <note>Faculty of Manufacturing and Mechatronic Engineering Technology</note>
  <note>Thesis (Master of Science) -- Universiti Malaysia Pahang – 2021</note>
  <note>Includes bibliographical references</note>
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      <namePart>Faculty of Manufacturing and Mechatronic Engineering Technology</namePart>
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  <identifier type="isbn">THE0009154(Local)</identifier>
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