参数时变的PMSM转速滑模观测器改进研究
Research on improvement of PMSM speed sliding mode observer with time-varying parameters
孟丽丽 1张正禹 1刘伟民 1代文1
作者信息
- 1. 华北理工大学 机械工程学院,河北 唐山 063210
- 折叠
摘要
针对永磁同步电机(PMSM)传统转速滑模观测器在运行过程中,因电机参数变化而导致的精度与性能下降,提出一种改进滑模观测器,将参数辨识与滑模观测器相结合.在转速滑模观测器运行过程中,基于粒子群优化(PSO)算法,实时对定子电阻、电感以及转子磁链进行辨识,并通过辨识值优化滑模观测器中的电机参数.此外,还抑制了PSO算法在高维度中的性能下降,提高了辨识精度与效率.通过仿真与实验,发现搭载参数辨识的改进滑模观测器,对电机运行中的参数变化与干扰具有更强的鲁棒性和更高的辨识精度.
Abstract
To address the decreasing accuracy and performance of the traditional speed sliding mode observer for Permanent Magnet Synchronous Motors (PMSM) caused by variations in motor parameters,this paper proposes an enhanced sliding mode observer,which integrates parameter identification with the sliding mode observer.During the operation of the speed sliding mode observer,the stator resistance,inductance,and rotor flux linkage are identified in real-time by employing the Particle Swarm Optimization (PSO) algorithm,and the motor parameters within the sliding mode observer are optimized based on the identified values.Furthermore,improvements are made to address the performance degradation of the PSO algorithm in high-dimensional problems,aiming to enhance its identification accuracy and efficiency.Our simulation and experimental validations demonstrate the enhanced sliding mode observer,integrated with parameter identification,exhibits a greater robustness against parameter variations and disturbances during motor operation with a higher identification accuracy.
关键词
永磁同步电机/滑模观测器/参数辨识/粒子群算法Key words
permanent magnet synchronous motor/sliding mode observer/parameter identification/PSO引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据