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

Xiaozhong Liao; Manjie Ran; Donghui Yu; Yong Wang; Da Lin

doi:10.1109/IECON51785.2023.10312608

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

School of Automation

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	IECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE Computer Society
ISBN (Electronic)	9798350331820
DOIs	https://doi.org/10.1109/IECON51785.2023.10312608
Publication status	Published - 2023
Event	49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023 - Singapore, Singapore Duration: 16 Oct 2023 → 19 Oct 2023

Publication series

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

Conference

Conference	49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023
Country/Territory	Singapore
City	Singapore
Period	16/10/23 → 19/10/23

Keywords

Caputo-Fabrizio derivative
chaos control
fractional-order Buck converter

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10.1109/IECON51785.2023.10312608

Cite this

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title = "Chaos Control of Fractional-Order Buck Converter Based on Caputo-Fabrizio Fractional Derivative",

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.",

keywords = "Caputo-Fabrizio derivative, chaos control, fractional-order Buck converter",

author = "Xiaozhong Liao and Manjie Ran and Donghui Yu and Yong Wang and Da Lin",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023 ; Conference date: 16-10-2023 Through 19-10-2023",

year = "2023",

doi = "10.1109/IECON51785.2023.10312608",

language = "English",

series = "IECON Proceedings (Industrial Electronics Conference)",

publisher = "IEEE Computer Society",

booktitle = "IECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society",

address = "United States",

}

Liao, X, Ran, M, Yu, D, Wang, Y & Lin, D 2023, Chaos Control of Fractional-Order Buck Converter Based on Caputo-Fabrizio Fractional Derivative. in IECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society. IECON Proceedings (Industrial Electronics Conference), IEEE Computer Society, 49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023, Singapore, Singapore, 16/10/23. https://doi.org/10.1109/IECON51785.2023.10312608

Chaos Control of Fractional-Order Buck Converter Based on Caputo-Fabrizio Fractional Derivative. / Liao, Xiaozhong; Ran, Manjie; Yu, Donghui et al.
IECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society. IEEE Computer Society, 2023. (IECON Proceedings (Industrial Electronics Conference)).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Chaos Control of Fractional-Order Buck Converter Based on Caputo-Fabrizio Fractional Derivative

AU - Liao, Xiaozhong

AU - Ran, Manjie

AU - Yu, Donghui

AU - Wang, Yong

AU - Lin, Da

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

KW - Caputo-Fabrizio derivative

KW - chaos control

KW - fractional-order Buck converter

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DO - 10.1109/IECON51785.2023.10312608

M3 - Conference contribution

AN - SCOPUS:85179523921

T3 - IECON Proceedings (Industrial Electronics Conference)

BT - IECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society

PB - IEEE Computer Society

T2 - 49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

Y2 - 16 October 2023 through 19 October 2023

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

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