基于神经网络逆解耦的异步电动机节能控制  

A New Energy Saving Method of Asynchronous Motor Based on Neural Network Inverse Decoupling

作　　者：汪科[1,2] 

机构地区：[1]广西科技大学,广西545006 [2]湖南铁道职业技术学院,湖南412001

出　　处：《微特电机》2016年第4期40-42,共3页Small & Special Electrical Machines

摘　　要：异步电动机矢量控制是一种稳态下的解耦控制,当对电机调节励磁进行节能控制时,及负载突变状态下系统解耦性能下降,节能效果变差。针对异步电动机节能控制中的上述问题,提出一种将基于神经网络逆系统方法的异步电动机解耦控制与基于损耗模型的节能控制策略相结合的异步电动机节能控制方法。仿真表明该方法具有较好的动态节能控制效果及较强的负载跟踪能力。The vector control of asynchronous motor adopts a kind of steady state decoupling control which will becomeless efficient in energy saving when in the dynamic procedure of excitation regulating or in the load change procedure. In order to solve the problem, a new energy saving method of asynchronous motor was proposed, which was a combinaion of neural network decoupling control of asynchronous motor with an optimizing strategy on loss model. The simulation proves thenew method has better results on energy saving in the dynamic procedure and load tracking capability.

关 键 词：异步电动机节能 神经网络逆解耦控制 损耗模型 

分 类 号：TM343[电气工程—电机]