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Development of a neuro-fuzzy controller for induction motor

机译:感应电动机的神经模糊控制器的开发

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This paper presents a novel neuro-fuzzy (NF) controller based speed control scheme for a high performance induction motor (IM) drive. A 5-layer ANN structure is utilized to train the parameters of the FLC based on the minimization of the square of the error, which is considered as the object function. The FLC and ANN structures were developed based on motor control theory incorporating various uncertainties. A complete simulation model for indirect field oriented control of IM incorporating the proposed NF controller is developed. The performance of the proposed NF based IM drive is investigated at different operating conditions such as sinusoid reference speed, load disturbance and parameter disturbances. It is found that the performance of the proposed drive is robust and suitable for application in high performance industrial drive applications.
机译:本文提出了一种新型的基于神经模糊(NF)控制器的高性能感应电动机(IM)驱动器的速度控制方案。基于误差平方的最小化,使用五层ANN结构来训练FLC的参数,这被认为是目标函数。 FLC和ANN结构是基于电动机控制理论并结合各种不确定性而开发的。建立了包含所提出的NF控制器的IM间接定向磁场控制的完整仿真模型。在不同的运行条件下(例如正弦参考速度,负载扰动和参数扰动)研究了建议的基于NF的IM驱动器的性能。发现所提出的驱动器的性能是鲁棒的并且适合于在高性能工业驱动器应用中的应用。

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