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FPGA resources reduction with multiplexing technique for implementation of ANN-based harmonics extraction by mp-q method

机译:用MP-Q方法实现FPGA资源,用多路复用技术实现基于ANN的谐波提取

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An novel multiplexing technique applied on a neural harmonics extraction method is presented in this paper. This structure can be used in nonlinear loads compensation with Active Power Filters. The approach is composed of a neural Phase Lock-Loop and a neural reference current generator based on an efficient formulation of the instantaneous reactive power theory. For the purpose of harmonics suppression and reactive power compensation, the whole architecture is composed of three Adaline Neural Networks whose structure leads to an important consumption of Field Programmable Gate Array resources during implementation. The presented technique uses only one Adaline and keeps the immunity of the proposed approach under non-sinusoidal and unbalanced conditions of voltage. Simulation results of the neural harmonics detection system connected to a reference current control shows balanced and sinusoidal source currents under various conditions. Results with experimental measurement made on an Active Power Filters test bench demonstrate its good performances on harmonics filtering. Moreover, the simple structure from the new approach called mp-q method shows a significant resource reduction.
机译:本文提出了一种在神经谐波提取方法上应用的新型多路复用技术。该结构可用于具有有源电力滤波器的非线性负载补偿。该方法基于瞬时无功功率理论的有效配方,由神经相锁环和神经参考电流发生器组成。出于谐波抑制和无功补偿的目的,整个架构由三个亚甘油神经网络组成,其结构在实现期间导致现场可编程门阵列资源的重要消耗。呈现的技术仅使用一个亚葡萄酒并在非正弦和不平衡的电压条件下保持所提出的方法的免疫力。连接到参考电流控制的神经谐波检测系统的仿真结果显示了各种条件下的平衡和正弦源电流。具有在有源电力过滤器测试台上进行实验测量的结果,展示了对谐波过滤的良好性能。此外,来自称为MP-Q方法的新方法的简单结构显示了显着的资源。

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