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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 7/2020

12.10.2018 | Original Article

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

verfasst von: Chih-Min Lin, Van-Hoa La, Tien-Loc Le

Erschienen in: Neural Computing and Applications | Ausgabe 7/2020

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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.
Vorheriger Artikel Computer-aided classification of the mitral regurgitation using multiresolution local binary pattern
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Metadaten
Titel
DC–DC converters design using a type-2 wavelet fuzzy cerebellar model articulation controller
verfasst von
Chih-Min Lin
Van-Hoa La
Tien-Loc Le
Publikationsdatum
12.10.2018
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 7/2020
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3755-z

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