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FPGA implementation of adaptive ANN controller for speed regulation of permanent magnet stepper motor drives

机译:自适应ANN控制器的FPGA实现,用于永磁步进电机驱动器的速度调节

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摘要

This paper presents a novel adaptive artificial neural network (ANN) controller, which applies on permanent magnet stepper motor (PMSM) for regulating its speed. The dynamic response of the PMSM with the proposed controller is studied during the starting process under the full load torque and under load disturbance. The effectiveness of the proposed adaptive ANN controller is then compared with that of the conventional PI controller. The proposed methodology solves the problem of nonlinearities and load changes of PMSM drives. The proposed controller ensures fast and accurate dynamic response with an excellent steady state performance. Matlab/Simulink tool is used for this dynamic simulation study. The main contribution of this work is the implementation of the proposed controller on field programmable gate array (FPGA) hardware to drive the stepper motor. The driver is built on FPGA Spartan-3E Starter from Xilinx. Experimental results are presented to demonstrate the validity and effectiveness of the proposed control scheme.
机译:本文提出了一种新型的自适应人工神经网络(ANN)控制器,该控制器应用于永磁步进电机(PMSM)来调节其速度。在启动过程中,在满负载转矩和负载扰动下,研究了带有建议控制器的PMSM的动态响应。然后将所提出的自适应ANN控制器的有效性与常规PI控制器的有效性进行比较。所提出的方法解决了PMSM驱动器的非线性和负载变化的问题。所提出的控制器可确保快速准确的动态响应以及出色的稳态性能。 Matlab / Simulink工具用于此动态仿真研究。这项工作的主要贡献是在现场可编程门阵列(FPGA)硬件上实施建议的控制器来驱动步进电机。该驱动程序基于Xilinx的FPGA Spartan-3E Starter构建。实验结果表明该控制方案的有效性和有效性。

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