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Power Factor Improvement by using Artificial Neural Network with Single Inductor Dual Output circuit implementation

机译:通过使用单电感器双输出电路实现使用人工神经网络的功率因数改进

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Today latest technologies have been used to reduce the losses of the existing system and slow down the rate of occurrence of global warming. Most of the designs and researches aim to improve the power quality of the system. Purpose to design this circuit for the power factor improvement single inductor dual output circuit used single source in input side with the dual or multiple output system. Now days the consumers uses electronic equipments in large amount that shows utilization of maximum or multiple output through the minimum input source. In this the PI controller circuit is reconstructed with the help of Artificial Neural Network as a controller with fly-back converter. The design also shows the comparison between the both (PI & ANN) controllers. Through output gives the regulated output supply, here this study about the artificial neural network is efficiently remove problems to improve the power factor and reduce more THD (i.e. total harmonic distortion). The Artificial neural network helps oscillation, overshooting and undershooting and provides light weight, less settling time, small size. Main purpose to design this circuit improving the power factor with ANN controller MATLAB simulation is used to design the circuit. This design is shows that the ANN controller is more accurate when compared to the conventional system.
机译:今天,最新技术已被用来降低现有系统的损失,减缓全球变暖的发生率。大多数设计和研究旨在提高系统的电能质量。目的要设计该电路的功率因数改进单电感器双输出电路用双或多输出系统的输入侧使用单源。现在,消费者使用大量的电子设备,显示通过最小输入源的最大或多个输出的利用。在此,利用人工神经网络作为具有卷返转换器的控制器的帮助重建PI控制器电路。设计还显示了两者(PI和ANN)控制器之间的比较。通过输出给出了受调节的输出电源,这里本关于人工神经网络的研究有效地消除了问题以改善功率因数,减少更多THD(即总谐波失真)。人工神经网络有助于振荡,过冲和下划线,并提供轻质,更少的稳定时间,小尺寸。设计该电路的主要目的是使用ANN控制器MATLAB仿真改进功率因数来设计电路。该设计表明,与传统系统相比,ANN控制器更准确。

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