@inproceedings{1bc2f912512a4fd8b5e2be184016f10e,
title = "Small Signal Modeling of Fractional-Order Boost Converter with Non-Singular Fractional Derivative",
abstract = "The fractional-order models have received extensive attention as they could describe the system characteristics of the Boost converter more accurately compared with integer-order models. Due to the singular kernels of traditional definitions that would reduce the modeling accuracy, this paper proposes a Caputo-Fabrizio (C-F) definition-based fractional-order Boost converter model using the small signal modeling method by employing equivalent state variables instead of traditional ones. The proposed model has high accuracy, which is verified by scanning the frequency of the circuit model and comparing it with the mathematical model. Additionally, the influence of fractional order on the system characteristics of the model in the frequency domain is analyzed, providing theoretical support for further studies on fractional-order boost converters with non-singular kernels.",
keywords = "Boost converter, Caputo-Fabrizio derivative, Fractional calculus, Small signal modeling",
author = "Donghui Yu and Xiaozhong Liao and Yong Wang and Manjie Ran and Da Lin",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 9th International Conference on Control, Decision and Information Technologies, CoDIT 2023 ; Conference date: 03-07-2023 Through 06-07-2023",
year = "2023",
doi = "10.1109/CoDIT58514.2023.10284234",
language = "English",
series = "9th 2023 International Conference on Control, Decision and Information Technologies, CoDIT 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "117--122",
booktitle = "9th 2023 International Conference on Control, Decision and Information Technologies, CoDIT 2023",
address = "United States",
}