A comparative study on particle swarm optimization and genetic algorithms for fixed order controller design

Faizullah Mahar*, Syed Saad Azhar Ali, Zuhaibuddin Bhutto

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This article deals with a performance evaluation of particle swarm optimization (PSO) and genetic algorithms (GA) for fixed order controller design. The major objective of the work is to compare the ability, computational effectiveness and efficiency to solve the optimization problem for both algorithms (PSO and GA). All simulation has been performed using a software program developed in the Matlab environment. As yet, overall results show that genetic algorithms generally can find better solutions compared to the PSO algorithm. The primary contribution of this paper is to evaluate the two algorithms in the tuning of proportional integral and derivative (PID)-controllers and minimization of cost function and maximization of robust stability in the servo system which represents a complex system. Such comparative analysis is very important for identifying both the advantages and their possible disadvantages.

Original languageEnglish
Title of host publicationEmerging Trends and Applications in Information Communication Technologies - Second International Multi Topic Conference, IMTIC 2012, Proceedings
Pages284-294
Number of pages11
DOIs
StatePublished - 2012
Externally publishedYes

Publication series

NameCommunications in Computer and Information Science
Volume281 CCIS
ISSN (Print)1865-0929

Keywords

  • Evolutionary algorithm
  • optimization
  • robustness performance and PID controller

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics

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