基于模糊控制的自适应超螺旋滑模观测器无传感器控制

Sensorless Control of Adaptive Super-twisting Sliding Mode Observer Based on Fuzzy Control

针对永磁同步电机传统超螺旋滑模观测器(Super-twisting algorithm based sliding-mode observer,STA-SMO)使用固定滑模参数,从而导致较大抖振和扰动抑制能力差的问题,提出了一种滑模参数可以随着系统转速变化而实时更新的永磁同步电机自适应超螺旋滑模观测器无位置传感器控制方法,并给出了所提方法的稳定性证明,通过在线调整滑模系数可以获得较高的估计精度。针对永磁同步电机传统矢量控制速度环采用固定参数PI控制器、无法满足系统快速响应和参数扰动抑制能力等问题,速度外环采用模糊PI控制器,通过模糊控制器的输出更新PI控制器的参数,增强系统的鲁棒性。最后,通过仿真和试验,验证了基于模糊控制的永磁同步电机自适应超螺旋滑模观测器可以有效抑制系统抖振,且估计精度高,鲁棒性强。

Aiming at the problem that the traditional super-twisting algorithm based sliding-mode observer(STA-SMO)of permanent magnet synchronous motor uses fixed sliding mode parameters,which leads to large chattering and poor disturbance rejection ability,a sensorless control method of permanent magnet synchronous motor adaptive super-helical sliding mode observer is proposed.The sliding mode parameters can be updated in real time with the change of system speed.The stability of the proposed method is proved,and the higher estimation accuracy can be obtained by adjusting the sliding mode coefficient online.Aiming at the problem that the traditional vector control speed loop of permanent magnet synchronous motor adopts fixed parameter PI controller,which cannot meet the rapid response and parameter disturbance suppression ability of the system,the fuzzy PI controller is used in the speed outer loop,and the parameters of the PI controller are updated by the output of the fuzzy controller to enhance the robustness of the system.Finally,through simulation and experiment,it is verified that the fuzzy control based adaptive super-twisting algorithm sliding-mode observer for permanent magnet synchronous motor can effectively suppress system chattering,with high estimation accuracy and strong robustness.