A novel chaotic fractional-order beetle swarm optimization algorithm and its application for load-frequency active disturbance rejection control

Yuemin Zheng, Zhaoyang Huang, Jin Tao*, Hao Sun, Qinglin Sun, Mingwei Sun, Matthias Dehmer, Zengqiang Chen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

This paper proposes a novel chaotic fractional-order beetle swarm optimization (CFBSO) algorithm that combines chaos concepts and a fractional derivative structure with the beetle swarm algorithm. The proposed CFBSO was compared with other advanced meta-heuristic algorithms on 23 benchmark functions with single-peak, multi-peak, and fixed-dimensional multi-peak optimization problems, and the effectiveness and superiority of the proposed algorithm were verified. The proposed CFBSO was then used to optimize the parameters of the active disturbance rejection controller (ADRC). The CFBSO-based ADRC was further applied for the load frequency control (LFC) system of a four-area interconnected power system consisting of a hydraulic turbine with a non-minimum phase (NMP) and three reheat turbines. The results showed that the proposed method had a smaller undershoot and shorter settling time than those obtained by a linear ADRC and a proportional–integral–derivative controller. Thus, it can meet the high-performance requirements of LFC.

Original languageEnglish
Number of pages5
JournalIEEE Transactions on Circuits and Systems II: Express Briefs
DOIs
Publication statusE-pub ahead of print - Jul 2021
MoE publication typeA1 Journal article-refereed

Keywords

  • active disturbance rejection control
  • beetle swarm optimization
  • Benchmark testing
  • chaotic fractional-order beetle swarm optimization
  • Circuits and systems
  • four-area interconnected power system
  • load frequency control.
  • Optimization
  • Particle swarm optimization
  • Sociology
  • Statistics
  • Sun

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