Research On Permanent Magnet Synchronous Motor Control Technology

With the continuous improvement of rare earth permanent magnet material extraction technology,Permanent Magnet Synchronous Machines(PMSMs)have been widely used in the field of servo turntables due to their high torque density and high efficiency.In traditional sensor-based control systems for PMSMs,sensors suffer from high cost,demanding operating environment requirements,and large size,leading to the research focus on sensorless control of PMSMs.To improve the control accuracy of sensorless PMSMs,this dissertation focuses on the control of surface-mounted permanent magnet synchronous machines using the fluxfrequency ratio(I/F)control with sliding mode observer.The research contents are as follows:Firstly,a summary and comparison of sensorless control methods for permanent magnet synchronous motors(PMSMs)were conducted,and the characteristics and applicability of different methods were analyzed.Based on this,in order to solve the problem of difficult sensorless start-up at zero speed and low speed,the I/F method was used for start-up,and then switched to sliding mode observer control in the medium and high-speed range.When switching from I/F control to sliding mode observer control,there will be differences in how the two algorithms handle the rotor position and stator current.Direct switching would result in unstable motor speed.Consequently,a transitional strategy with smooth interpolation was used in the dissertation to effectively improve the motor’s control performance.Secondly,an in-depth analysis of the inherent chattering problem in traditional sliding mode observer control was conducted.This was mitigated by introducing an adjustable quasisliding mode function in the improved control algorithm.In addition,the traditional sliding mode observer algorithm uses fixed gains,which cannot adapt to different speed requirements.Consequently,an improved super-twisting sliding mode observer was designed in the dissertation,with the error current as the input variable,further reducing tracking errors and improving the system’s dynamic performance and stability.Based on theoretical analysis and modeling simulations,compared to the control system using traditional sliding mode observer,the improved method proposed in this dissertation can effectively enhance the system’s dynamic performance.Finally,an experimental platform is built,and experimental verification and result comparison analysis are carried out on traditional sliding mode observer control,sliding mode observer control based on PLL(Phase Locked Loop),and improved super-twisting sliding mode observer control.The results show that the method proposed in this dissertation can better estimate the speed and track the position information of the motor,reflecting the effectiveness of this algorithm.