基于现场可编程门阵列(FPGA)的神经网络实现感应电机驱动定子磁链定向矢量控制

A. M. Soares, L. Leite, J. Pinto, Luiz E. B. da Silva, B. Bose, Milton E. Romero
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引用次数: 18

摘要

在这项工作中,提出了使用现场可编程门阵列(FPGA)实现SFOVC-ANN。该方案保证了神经网络的并行处理,因为电路设计是这样做的,在同一层的神经元并行处理输入信号。非线性s型传递函数采用样条插值实现,保证了较好的精度。摘要首先对所提出的系统进行了描述。然后,阐述了非线性神经元的实现策略。接着,介绍了人工神经网络的FPGA实现。最后给出了仿真和实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Field Programmable Gate Array (FPGA) Based Neural Network Implementation of Stator Flux Oriented Vector Control of Induction Motor Drive
In this work, it is proposed the implementation of the SFOVC-ANN using field programmable gate array (FPGA). The proposed scheme assure parallel processing of the ANN, since the circuit design was done in such way that the neurons in the same layer processes the input signals in parallel. The non-linear sigmoidal transfer function is implemented using Spline Interpolation, which guarantees an excellent precision. Initially in the digest, a description of the proposed system is given. Then, the nonlinear neuron implementation strategy is explained. Following this, the FPGA implementation of ANN is described. Finally, simulation and experimental results are given to substantiate the development.
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