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

被引:19
|
作者
Lin, Chih-Min [1 ]
La, Van-Hoa [1 ,2 ]
Le, Tien-Loc [1 ,2 ]
机构
[1] Yuan Ze Univ, 135 Yuandong Rd, Taoyuan 320, Taiwan
[2] Lac Hong Univ, Dept Elect Elect & Mech Engn, Bien Hoa, Vietnam
来源
NEURAL COMPUTING & APPLICATIONS | 2020年 / 32卷 / 07期
关键词
Type-2 fuzzy system; Cerebellar model articulation controller; DC-DC converter; Buck-boost converter; CONTROL-SYSTEM DESIGN; INTERVAL TYPE-2; NEURAL-NETWORK; MPPT;
D O I
10.1007/s00521-018-3755-z
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:2217 / 2229
页数:13
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