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永磁同步电机的模糊高斯基神经网络控制
Permanent Magnet Synchronous Motor Control Based on Fuzzy Guass Function Neural Network
【摘要】 本文将模糊控制与神经网络相结合,用神经网络来实现模糊推理,提出了一种把高斯基函数作为隶属函数的模糊神经网络,并将之用于永磁同步电机的控制中,利用神经网络的学习能力来达到调整模糊隶属函数和控制规则的目的,从而使控制系统得到更好的性能。仿真结果表明基于模糊高斯基函数神经网络控制的永磁同步电机控制系统与普通Fuzzy控制相比具有较快的响应速度、较高的稳态精度和较强的鲁棒性。
【Abstract】 In this paper,a fuzzy neural network is presented to control PMSM system in which fuzzy logic control and neural network are combined,fuzzy inference is realized by neural network,and Guass function is used as the membership function.The learning ability of neural network is used for the purpose of adjusting the membership function and the control rules,so that the control system can perform better. The simulation results show that the permanent magnet synchronous motor control system based on the fuzzy neural network control has quicker response speed,higher steady accuracy and better robustness.
【Key words】 fuzzy neural network; Guass function; Permanent magnet synchronous motor;
- 【文献出处】 微计算机信息 ,Microcomputer Information , 编辑部邮箱 ,2009年34期
- 【分类号】TM341;TP183
- 【被引频次】1
- 【下载频次】116