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Design of intelligent power controller for DC–DC converters using CMAC neural network

机译:基于CMAC神经网络的DC-DC变换器智能电源控制器设计。

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DC–DC converters are the devices which can convert a certain electrical voltage to another level of electrical voltage. They are very popularly used because of the high efficiency and small size. This paper proposes an intelligent power controller for the DC–DC converters via cerebella model articulation controller (CMAC) neural network approach. The proposed intelligent power controller is composed of a CMAC neural controller and a robust controller. The CMAC neural controller uses a CMAC neural network to online mimic an ideal controller, and the robust controller is designed to achieve L 2 tracking performance with desired attenuation level. Finally, a comparison among a PI control, adaptive neural control and the proposed intelligent power control is made. The experimental results are provided to demonstrate the proposed intelligent power controller can cope with the input voltage and load resistance variations to ensure the stability while providing fast transient response and simple computation.
机译:DC-DC转换器是可以将某个电压转换为另一个电压电平的设备。由于它们的高效率和小尺寸,它们非常受欢迎。本文通过小脑模型关节控制器(CMAC)神经网络方法为DC-DC转换器提出了一种智能功率控制器。提出的智能功率控制器由CMAC神经控制器和鲁棒控制器组成。 CMAC神经控制器使用CMAC神经网络在线模拟理想控制器,而鲁棒控制器则设计为以所需的衰减水平实现L 2 跟踪性能。最后,对PI控制,自适应神经控制和拟议的智能功率控制进行了比较。实验结果表明,所提出的智能功率控制器可以应对输入电压和负载电阻的变化,以确保稳定性,同时提供快速的瞬态响应和简单的计算。

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