A 5-degrees-of-freedom bearingless induction motor is a multi-variable,nonlinear and strong-coupled system．In order to achieve rotor suspension and operation steadily,it is necessary to realize dynamic decoupling con...A 5-degrees-of-freedom bearingless induction motor is a multi-variable,nonlinear and strong-coupled system．In order to achieve rotor suspension and operation steadily,it is necessary to realize dynamic decoupling control among torque and suspension forces．In the paper,a method based on α-th order inverse system theory is used to study dynamic decoupling control．Firstly,the working principles of a 3-degrees-of-freedom magnetic bearing and a 2-degrees-of-freedom bearinglees induction motor are analyzed, the radial-axial force equations of 3-degrees-of-freedom magnetic bearing,the electromagnetic torque equation and radial force equations of the 2-degrees-of-freedom bearingless induction motor are given,and then the state equations of the 5-degrees-of-freedom bearingless induction motor are set up．Secondly,the feasibility of decoupling control based on dynamic inverse theory is discussed in detail,and the state feedback linearization method is used to decouple and linearize the system．Finally,linear control system techniques are applied to these linearization subsystems to synthesize and simulate．The simulation results have shown that this kind of control strategy can realize dynamic decoupling control among torque and suspension forces of the 5-degrees-of-freedom bearingless induction motor,and that the control system has good dynamic and static performance．展开更多
基金Supported by National Natural Science Foundation of P.R.China(50575099,60674095)
文摘A 5-degrees-of-freedom bearingless induction motor is a multi-variable,nonlinear and strong-coupled system．In order to achieve rotor suspension and operation steadily,it is necessary to realize dynamic decoupling control among torque and suspension forces．In the paper,a method based on α-th order inverse system theory is used to study dynamic decoupling control．Firstly,the working principles of a 3-degrees-of-freedom magnetic bearing and a 2-degrees-of-freedom bearinglees induction motor are analyzed, the radial-axial force equations of 3-degrees-of-freedom magnetic bearing,the electromagnetic torque equation and radial force equations of the 2-degrees-of-freedom bearingless induction motor are given,and then the state equations of the 5-degrees-of-freedom bearingless induction motor are set up．Secondly,the feasibility of decoupling control based on dynamic inverse theory is discussed in detail,and the state feedback linearization method is used to decouple and linearize the system．Finally,linear control system techniques are applied to these linearization subsystems to synthesize and simulate．The simulation results have shown that this kind of control strategy can realize dynamic decoupling control among torque and suspension forces of the 5-degrees-of-freedom bearingless induction motor,and that the control system has good dynamic and static performance．
文摘针对无轴承异步电机(bearinglessinductionmotor,BL-IM)速度传感器故障识别问题,提出一种基于反向传播神经网络(back propagation neural network,BPNN)的故障诊断控制策略。首先,选取BL-IM转矩、相电流等信号作为BPNN传感器故障诊断依据,并利用传感器在不同故障下的转矩等故障数据样本不断地对BPNN进行训练学习,提高故障诊断及故障分类的准确率。其次,利用分数阶模型参考自适应控制(fractional order model reference adaptive system,FO-MRAS)建立无速度传感器容错控制系统,完成故障系统到容错控制系统的切换,最终实现BL-IM在传感器故障下的正常运行。仿真和实验结果均表明,提出的BPNN故障诊断系统不仅能够实现空载以及带载运行时速度传感器故障的准确识别,并且容错控制系统能显著降低传感器故障对转速的影响,同时电机悬浮转子也具有较好的悬浮特性,提高了BL-IM的安全性和可靠性。
