Abstract Neural Network (NN) based Least Mean Square (LMS)–Least Mean Fourth (LMF) control technique is developed and implemented in Field Programmable Gate Array (FPGA) for Shunt Active Power Filter (SAPF) to enhance Power Quality (PQ) in three-phase four wire distribution system. The PQ enhancement comprises the improvement of power factor, mitigation of harmonics and compensation of reactive power. The proposed control strategy is simulated in MATLAB/Simulink to determine the reference source currents and weights of active and reactive components. The simulation results of LMS–LMF control are compared with the other three control strategies. The NN control is developed as individual modules in FPGA. Thus it can be configured to any other research area which has identical requirements. The FPGA implementation overcomes the drawback of conventional controllers with a fast and accurate response. The FPGA based proposed control strategy for SAPF is developed as a laboratory prototype and the results obtained are analyzed. The results attained adhere to power quality standards.

中文翻译：

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基于 NN 的 LMS-LMF 控制算法在 DSTATCOM 中的 FPGA 实现以改善电能质量

摘要 基于神经网络 (NN) 的最小均方 (LMS)-最小均四 (LMF) 控制技术被开发并在现场可编程门阵列 (FPGA) 中实现，用于并联有源电力滤波器 (SAPF) 以提高电力质量 (PQ)三相四线配电系统。PQ 增强包括提高功率因数、减少谐波和补偿无功功率。建议的控制策略在 MATLAB/Simulink 中进行仿真，以确定参考源电流和有功和无功组件的权重。LMS-LMF 控制的仿真结果与其他三种控制策略进行了比较。NN 控制是作为 FPGA 中的独立模块开发的。因此，它可以配置到具有相同要求的任何其他研究领域。FPGA 实现克服了传统控制器具有快速准确响应的缺点。基于 FPGA 的 SAPF 控制策略被开发为实验室原型，并对获得的结果进行了分析。获得的结果符合电能质量标准。