Fractional-order PID controller optimization via improved electromagnetism-like algorithm

Ching Hung Lee*, Fu Kai Chang

*Corresponding author for this work

Research output: Contribution to journalArticle

121 Scopus citations

Abstract

Based on the electromagnetism-like algorithm, an evolutionary algorithm, improved EM algorithm with genetic algorithm technique (IEMGA), for optimization of fractional-order PID (FOPID) controller is proposed in this article. IEMGA is a population-based meta-heuristic algorithm originated from the electromagnetism theory. It does not require gradient calculations and can automatically converge at a good solution. For FOPID control optimization, IEMGA simulates the "attraction" and "repulsion" of charged particles by considering each controller parameters as an electrical charge. The neighborhood randomly local search of EM algorithm is improved by using GA and the competitive concept. IEMGA has the advantages of EM and GA in reducing the computation complexity of EM. Finally, several illustration examples are presented to show the performance and effectiveness.

Original languageEnglish
Pages (from-to)8871-8878
Number of pages8
JournalExpert Systems with Applications
Volume37
Issue number12
DOIs
StatePublished - Dec 2010

Keywords

  • Electromagnetism-like algorithm
  • Fractional-order PID control
  • Genetic algorithm
  • PID control

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