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Time-invariant and time-varying filters versus neural approach applied to DC component estimation in control algorithms of active power filters

机译:时间不变和时变的滤波器与有源电力滤波器控制算法中的DC分量估计应用于DC分量估计

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摘要

This paper presents an application of digital filters and neural networks to the extraction of a DC signal component. This problem arises, among others, in control of active power filters (APF) used for power quality improvement. Solutions to the basic problem of DC component estimation are well-known and so the difficulty of the task comes rather from the required minimization of the calculation time. It should ensure fast reaction of the control system to load changes. As a result, lower value of the current total harmonic distortion coefficient (THD) and better efficiency of the APF can be obtained.
机译:本文介绍了数字滤波器和神经网络的应用,以提取DC信号分量。 其中出现了用于控制电能质量改进的有源电力滤波器(APF)的问题。 DC分量估计的基本问题的解决方案是众所周知的,因此任务的难度来自计算时间的所需最小化。 它应确保控制系统的快速反应加载变化。 结果,可以获得电流总谐波失真系数(THD)的较低值和APF的更好效率。

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