Abstract This paper proposes a novel artificial neural network (ANN) control based shunt active power filter (APF) applied in aircraft power utility of 400 Hz. The model of shunt active power filter has been optimized using Adaptive Tabu search (ATS) algorithm and Genetic Algorithm (GA). ATS algorithm has been used to obtain the optimum value of K P and K I ; because Genetic Algorithm is applied to find the optimum value of filter inductor. The improvement in the control scheme using ANN control makes APF versatile for compensation of reactive power, harmonic currents, and other issues. This model compares from a simple ANN control model. The simulated results using MATLAB clearly prove the effectiveness of the proposed control method of aircraft shunt APF.

中文翻译：

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使用神经网络控制的自适应禁忌搜索和遗传算法优化并联有源电力滤波器的性能评估，用于 400 Hz 的飞机电源

摘要 本文提出了一种新型的基于人工神经网络（ANN）控制的并联有源电力滤波器（APF），应用于400Hz的飞机电源。采用自适应禁忌搜索（ATS）算法和遗传算法（GA）对并联有源电力滤波器模型进行了优化。已使用ATS算法获得KP和KI的最佳值；因为应用遗传算法来寻找滤波电感的最佳值。使用 ANN 控制的控制方案的改进使 APF 可用于补偿无功功率、谐波电流和其他问题。该模型与简单的 ANN 控制模型进行比较。利用MATLAB的仿真结果清楚地证明了所提出的飞机分流APF控制方法的有效性。