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The iterative learning control strategy for hybrid active filter to dampen harmonic resonance in industrial power system

机译:混合有源滤波器抑制工业电力系统谐波谐振的迭代学习控制策略。

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This paper introduces application of iterative learning control strategy to hybrid active filter with the purpose of damping harmonics resonance in industrial power system. The control strategy can facilitate optimizing performance of damping harmonics resonance due to combination of feedback and feedforward learning control. In the hybrid filter, to obtain the proper reference voltage for voltage-source inverter based active filter, the feedback control scheme mainly focuses on the compensation of reactive power harmonic current and feedforward learning control puts its attention on tracking source voltage distortion and load harmonic current as fast as possible. The control strategy can also simplify configuration of the controller with only source current viewpoints and easy algorithm. The paper still establishes a set of strategy to self-optimizing performance of the system, and presents more useful criteria for identification of stable state of system incorporating reduction of THD of source current corresponding to reference voltage. Some simulation and experimental results based on 12-pulse rectifier system examined are given in the paper.
机译:本文介绍了迭代学习控制策略在混合有源滤波器中的应用,其目的是抑制工业电力系统中的谐波谐振。由于反馈和前馈学习控制的结合,该控制策略可有助于优化阻尼谐波谐振的性能。在混合滤波器中,为了为基于电压源逆变器的有源滤波器获得合适的参考电压,反馈控制方案主要侧重于无功谐波电流的补偿,前馈学习控制将重点放在跟踪源电压失真和负载谐波电流上。尽可能快地。该控制策略还可以仅通过源电流观点和简单算法来简化控制器的配置。本文仍然建立了一套系统自我优化性能的策略,并提出了更有用的准则来识别系统的稳定状态,其中包括降低与参考电压相对应的源电流的THD。给出了基于12脉冲整流器系统的一些仿真和实验结果。

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