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感应电机的新型神经网络广义逆系统解耦控制
引用本文:刘陆洲,肖建,王嵩.感应电机的新型神经网络广义逆系统解耦控制[J].电机与控制学报,2009,13(Z1).
作者姓名:刘陆洲  肖建  王嵩
作者单位:西南交通大学电气工程学院,四川成都,610031
基金项目:国家自然科学基金资助项目,高等学校博士学科点专项科研基金资助项目 
摘    要:针对感应电机这一多变量、强耦合系统,提出了一种新型神经网络广义逆系统解耦控制方法,给出了新型广义逆系统的存在性证明.它与感应电机复合,将转子磁链与转速的解耦成两个独立的伪线性子系统,并且可以随时通过调整反馈参数改变两个伪线性子系统的配置极点,为控制器的设计提供了便利.仿真结果表明,通过合理的选择配置极点和控制器参数,整个控制系统对电机参数变化和负载扰动有较强的鲁棒性和动态性能.

关 键 词:解耦控制  广义逆系统  神经网络  鲁棒性

Decoupling control of induction motor based on a new type of ANN generalized inverse
LIU Lu-zhou,XIAO Jian,WANG Song.Decoupling control of induction motor based on a new type of ANN generalized inverse[J].Electric Machines and Control,2009,13(Z1).
Authors:LIU Lu-zhou  XIAO Jian  WANG Song
Abstract:A decoupling control method based on a new type of artificial neural network (ANN) generalized inverse is proposed for induction motor which is a multivariable and high coupling system. The existence of the new type of generalized inverse was proved. The composition of the generalized inverse and the inductor motor decoupled the rotor flux and rotor speed into two independent pseudo-linear subsystems ,the poles of which can be assigned anytime by regulating the feedback parameters which were beneficial to the design of controller. Simulation results show that the whole control system has strong robustness to variation of motor parameters and load torque disturbance by assigning poles and choosing parameter of the controller appropriately.
Keywords:decoupling control  generalized inverse  artificial neural network  robustness
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