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DC–DC converters design using a type-2 wavelet fuzzy cerebellar model articulation controller

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Abstract

Recently, boost and buck converters are widely applied in many applications, especially in recycled energy industry. The efficiency of DC–DC converter, which can increase or decrease the input voltage according to the driver output voltage, can effectively affect the total efficiency of the systems. In this paper, a sliding mode interval type-2 fuzzy wavelet cerebellar model articulation controller (T2WFCMAC)-based control system is designed for the DC–DC converters. The proposed control system contains a main controller and a robust compensation controller. The main controller is the T2WFCMAC which is used to mimic an ideal controller, and the robust compensation is designed to compensate for the approximation error between the main controller and the ideal controller. The sliding hyperplane is applied to improve the robustness of the control system. All the adaptive laws for adjusting the parameters of T2WFCMAC are obtained using the gradient descent method. The stability of control system is guaranteed in the sense of Lyapunov function. Finally, numerical experimental results of boost and buck converters are presented to illustrate the effectiveness of the proposed approach under the change in the input voltage and the load resistance variations.

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Acknowledgements

The authors appreciate the financial support in part from the Nation Science Council of Republic of China under Grant NSC 101-2221-E-155-026-MY3.

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Authors and Affiliations

  1. Yuan Ze University, No. 135, Yuandong Rd., Chung-Li, Taoyüan, 320, Taiwan, ROC

    Chih-Min Lin, Van-Hoa La & Tien-Loc Le

  2. Department of Electrical Electronic and Mechanical Engineering, Lac Hong University, Bien Hoa, Vietnam

    Van-Hoa La & Tien-Loc Le

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  1. Chih-Min Lin
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  2. Van-Hoa La
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Correspondence to Chih-Min Lin.

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Lin, CM., La, VH. & Le, TL. DC–DC converters design using a type-2 wavelet fuzzy cerebellar model articulation controller. Neural Comput & Applic 32, 2217–2229 (2020). https://doi.org/10.1007/s00521-018-3755-z

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  • DOI: https://doi.org/10.1007/s00521-018-3755-z

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