Chaos Control of Fractional-Order Buck Converter Based on Caputo-Fabrizio Fractional Derivative

Xiaozhong Liao, Manjie Ran*, Donghui Yu, Yong Wang, Da Lin

*Corresponding author for this work

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

Abstract

This paper presents, for the first time, a chaos control scheme for the fractional-order Buck converter with Caputo-Fabrizio derivative to suppress the chaos phenomenon. Chaos analysis of the peak current mode fractional-order Buck converter is first carried out by numerical simulation, with a focus on the impact of the fractional order on the system's chaos range. A chaos controller based on a genetic algorithm optimized neural network is then proposed, which combines the neural network algorithm with the parametric resonance perturbation method to optimize the design of control parameters. Finally, circuit simulations in MATLAB show that the proposed method effectively controls the system from a chaotic state to a stable state, demonstrating the effectiveness of the chaos control algorithm used in this paper.

Original languageEnglish
Title of host publicationIECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE Computer Society
ISBN (Electronic)9798350331820
DOIs
Publication statusPublished - 2023
Event49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023 - Singapore, Singapore
Duration: 16 Oct 202319 Oct 2023

Publication series

NameIECON Proceedings (Industrial Electronics Conference)
ISSN (Print)2162-4704
ISSN (Electronic)2577-1647

Conference

Conference49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023
Country/TerritorySingapore
CitySingapore
Period16/10/2319/10/23

Keywords

  • Caputo-Fabrizio derivative
  • chaos control
  • fractional-order Buck converter

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