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IJML 2012 Vol.2(3): 345-350
doi: 10.7763/IJMLC.2012.V2.142

EOTs Based Fixed Order Controller Design and Performance Analysis

Faizullah Mahar1 , Saad Azhar Ali2 , Ayaz Hussain1 , Zohaibdin Bhutto1

  • 1Balochistan University of Engineering and Technology, Khuzdar, Pakistan.
  • 2Electronic Engineering Department, Iqra University

Abstract

Evolutionary optimizations techniques (EOTs) are stochastic search techniques that direct a population of solutions towards best possible results by using the natural principles. In recent years, these algorithms have grown to be an accepted optimization tool for many areas of scientific and engineering research, together with control system engineering design. Significant research exists concerning evolutionary algorithms to control system design and robustness performance analysis of controller. But, little work has been done with evolutionary optimization algorithms because of the problems related with robustness performance in early period of the evolution of controllers. Moreover, until recently the robustness performance of controllers based on evolutionary algorithms has not been researched in stipulate. The scope of this research covers generalized robustness performance condition and detailed analysis of the resultant control system.

Keywords

  • Evolutionary algorithm
  • optimization
  • robustness
  • performance and controller
142-L1010

How to Cite

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Faizullah Mahar, Saad Azhar Ali, Ayaz Hussain, and Zohaibdin Bhutto, "EOTs Based Fixed Order Controller Design and Performance Analysis," International Journal of Machine Learning, vol. 2, no. 3, pp. 345-350, 2012. https://doi.org/10.7763/IJMLC.2012.V2.142

Copyright & License

Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • DOI: 10.18178/IJML
  • Frequency: Quarterly
  • Average Days to Accept: 68 days
  • Acceptance Rate: 27%
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • DOI: 10.18178/IJML
  • Abstracing/Indexing: Google Scholar, Crossref, ProQuest, Electronic Journals Library, CNKI.
  • E-mail: editor@ijml.org
  • APC: 500USD