Fractional Order PID Design based on Novel Improved Slime Mould Algorithm

Davut Izci*, Serdar Ekinci, H. Lale Zeynelgil, John Hedley

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

36 Citations (Scopus)

Abstract

This study attempts to maintain the terminal voltage level of an automatic voltage regulator (AVR) and control the speed of a direct current (DC) motor using a fractional order proportional integral derivative (FOPID) controller. The best parameters of the controller have been adjusted using a novel meta-heuristic algorithm called opposition-based hybrid slime mold with simulated annealing algorithm. The proposed algorithm aims to improve the original slime mold algorithm in terms of exploitation and exploration using simulated annealing and opposition-based learning, respectively. A time domain objective function was adopted as performance index to design the FOPID-based AVR and DC motor systems. The initial performance evaluation was carried out using unimodal and multimodal benchmark functions. The results confirmed the superior exploration and exploitation capabilities of the developed algorithm compared to the other state-of-the-art optimization algorithms. The performance of the proposed algorithm has also been assessed through statistical tests, time domain and frequency domain simulations along with robustness and disturbance rejection analyses for both DC motor and AVR systems. The proposed algorithm has shown superior capabilities for the respective systems compared to the other state-of-the-art optimization algorithms used for the same purpose.

Original languageEnglish
Pages (from-to)901-918
Number of pages18
JournalElectric Power Components and Systems
Volume49
Issue number9-10
DOIs
Publication statusPublished - 2021

Bibliographical note

Publisher Copyright:
© 2022 Taylor & Francis Group, LLC.

Keywords

  • DC motor
  • FOPID controller
  • automatic voltage regulator
  • opposition-based learning
  • simulated annealing
  • slime mold algorithm

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