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An ANN Based X-PC Target Controller for Speed Control of Permanent Magnet Brushless DC Motor

机译:永磁无刷直流电机速度控制的基于ANN的X-PC目标控制器

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In this paper an Artificial Neural Net (ANN) is suggested for implementation as a reference commutation signal generator for speed control of Permanent Magnet Brushless DC Motor in X-PC target domain in overloaded condition. The ANN is trained in the continuous time and then it is transformed to discrete time. The reason for this transformation is that the X-PC Target accepts only discrete models. The ANN is initially optimised by obtaining continuous time domain data by experimentation. Since the actual system is an embedded system hence the ANN is transformed to discrete model and then it is interfaced to the transfer function model of PMBLDC motor to analyse its performance. After optimisation the system is targeted for a X-PC target by discritising the model for a specified sampling rate based on the performance of the Interface card. The system is tested in Real Time and is working as designed. The system is responding to the overload conditions in an almost linearised manner which is not the normal characteristics of the PMBLDC motor.
机译:在本文中,建议实施人工神经网络(ANN)作为参考换向信号发生器,用于在过载状态下X-PC目标域的永磁无刷直流电动机的速度控制。 ANN在连续时间训练,然后转变为离散时间。这种转换的原因是X-PC目标仅接受离散模型。通过实验获得连续时间域数据,最初优化了ANN。由于实际系统是嵌入式系统,因此ANN被转换为离散模型,然后它与PMBLDC电机的传递函数模型接口以分析其性能。优化后,通过基于接口卡的性能,通过对指定采样率的模型进行分解模型来针对X-PC目标。系统实时测试,并按照设计工作。该系统以几乎线性的方式响应过载条件,这不是PMBLDC电机的正常特性。

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