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
N1 - Publisher Copyright:
© 2023 IEEE.
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
UR - http://www.scopus.com/inward/record.url?scp=85179523921&partnerID=8YFLogxK
U2 - 10.1109/IECON51785.2023.10312608
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
ER -