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

机译:DC-DC转换器设计使用Type-2小波模糊大脑模型铰接控制器

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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.
机译:最近,提升和降压转换器广泛应用于许多应用,特别是在再生能源行业中。 DC-DC转换器的效率可以根据驾驶员输出电压增加或减小输入电压,可以有效地影响系统的总效率。在本文中,为DC-DC转换器设计了一种滑动模式间隔类型-2模糊小波大脑模型铰接控制器(T2WFCMAC)的控制系统。所提出的控制系统包含主控制器和鲁棒补偿控制器。主控制器是用于模拟理想控制器的T2WFCMAC,鲁棒补偿旨在补偿主控制器和理想控制器之间的近似误差。施加滑动超平板以改善控制系统的鲁棒性。使用梯度下降方法获得用于调整T2WFCMAC参数的所有自适应规律。 Lyapunov函数的感觉,保证了控制系统的稳定性。最后,提出了升压和降压转换器的数值实验结果,以说明在输入电压的变化和负载电阻变化下提出的方法的有效性。

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