Efficient design of wideband digital fractional order differentiators and integrators using multi-verse optimizer

Talal Ahmed Ali Ali, Zhu Xiao, Seyedali Mirjalili, Vincent Havyarimana

Research output: Contribution to journalArticle

Abstract

In this paper, a novel method is proposed based on combining L1-norm optimally criterion with a recently-proposed metaheuristic called multi-verse optimizer (MVO) to design 2nd–4th order stable, minimum phase and wideband infinite impulse response (IIR) digital fractional order differentiators (DFODs) for the fractional order differentiators (FODs) of one-half, one-third and one-fourth order. To confirm the superiority of the proposed approach, we conduct comparisons of the MVO-based designs with the real-coded genetic algorithm (RCGA) and particle swarm optimization (PSO)-based designs in terms of accuracy, robustness, consistency, and efficiency. The transfer functions of the proposed designs are inverted to obtain new models of digital fractional order integrators (DFOIs) of the same order. A comparative study of the frequency responses of the proposed digital fractional order differentiators and integrators with the ones of the existing models is then conducted. The results demonstrate that the proposed designs yield the optimal magnitude responses in terms of absolute magnitude error (AME) with flat response profiles.

Original languageEnglish
Article number106340
JournalApplied Soft Computing Journal
Volume93
DOIs
Publication statusPublished - Aug 2020

Keywords

  • Digital fractional order differentiator
  • Digital fractional order integrator
  • Genetic Algorithm
  • L-norm
  • Metaheuristic
  • Multi-verse optimizer
  • Optimization
  • Particle Swarm Optimization

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