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首页> 外文期刊>Journal of intelligent & fuzzy systems: Applications in Engineering and Technology >A comparative simulation study of different sensorless permanent magnet synchronous motor drives using neural network and fuzzy logic
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A comparative simulation study of different sensorless permanent magnet synchronous motor drives using neural network and fuzzy logic

机译：基于神经网络和模糊逻辑的不同无传感器永磁同步电动机驱动的比较仿真研究

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摘要

This paper deals with MATLAB/SIMULINK simulation and analysis of a position sensor-less field oriented control of permanent magnet synchronous motor. Adaptive position estimators are required as the parameters of the machines like rotor resistance, inductance changes sometimes. Adaptive position and speed estimators viz. SMO, MRASare much discussed in literature but the artificial neural network, adaptive neuro-fuzzy inference based estimators are least discussed. In this paper a MATLAB study of MRAS, ANN and ANFIS based position estimator in a Field oriented control of a permanent magnet synchronous motor drive is being done. MRAS, ANN, ANFIS estimators adaptive in nature so these estimators can adapt if there is any parameters change online. The performances of these three drives are analyzed, and results are compared. It is seen that ANFIS based system performance is better even when the parameters of the machines vary with time. This work is limited to analysis and simulation only and could be extended to a practical realization in future work.
机译：本文涉及MATLAB / SIMULINK仿真和分析永磁同步电动机的位置传感器 - 较较低的场面向控制。自适应位置估计是作为转子电阻等机器的参数所必需的，有时电感会发生变化。自适应位置和速度估算器viz。 Smo，MarraSare在文献中讨论了人工神经网络，基于自适应神经模糊推断的估算器是最不讨论的。在本文中，正在进行一个MATLAB研究的MRAR，ANN和ANFI基于ANFI的位置估计的永磁同步电动机驱动器的磁场控制控制。 MRAS，ANN，ANFIS估计在自然界中自适应，因此这些估算器可以适应如果有任何参数在线更改。分析了这三个驱动器的性能，并比较了结果。可以看出，即使当机器的参数随时间而变化时，基于ANFIS的系统性能也更好。这项工作仅限于分析和模拟，并且可以扩展到未来工作的实际实现。

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