感应型无轴承电动机的模糊神经网络控制系统

Research of Induction Type Bearingless Motor's Magnetic Suspension Control Using Fuzzy Neural Network

由于负载、干扰和径向位移检测误差,无轴承电动机悬浮运行时定、转子中心并不重合,产生偏心,影响了其稳定悬浮控制性能。从运行原理出发,建立了感应型无轴承电动机磁悬浮力的解析模型,并采用模糊神经网络对其进行控制,有效地提高了感应型无轴承电动机稳定悬浮运行的动、静态性能。

Due to the load disturbance and detecting error of radial displacement, the centers of stator and rotor of a bearingless motor do not coincide with each other in practical operation, which will influence the control performance of stable suspension. Based on its operation principle, a relatively accurate analytical expression of the magnetic levitation force for an induction-type bearingless motor is proposed with the eccentricity in the location of stator and rotor taking into consideration. And using fuzzy neural network control the induction-type bearingless motor. Simulation study verifies the effectiveness of the approach in improving the static and dynamic performance of an induction-type bearing-less motor.