摘要
针对中低速情况下双三相永磁同步电机无传感器控制精度低,非线性磁链观测器在静止和低速时稳定性差的问题,提出一种结合BP神经网络的离散型非线性磁链观测器。首先,结合电流方程构建非线性磁链观测器并利用欧拉离散法进行离散化;其次,采用BP神经网络优化非线性磁链的固定增益,实现增益在线调节,同时提出自适应高频信号注入方法,解决了非线性磁链观测器受固定增益值限制观测误差大和低速情况下稳定性差的问题;最后,在MATLAB环境下搭建了仿真模型验证提出的算法,并且仿真结果显示新型观测器的位置误差减小了37.5%以上,收敛速度提升了50%以上,有效地抑制系统抖振,具有更强的鲁棒性。
Aiming at the problems of low sensorless control accuracy and poor stability of nonlinear flux observer at static and low speed,a discrete nonlinear flux observer combined with BP neural network was proposed.Firstly,the nonlinear flux observer is constructed by combining the current equation and discretized by the Euler discretization method.Secondly,BP neural network is used to optimize the fixed gain of the nonlinear flux observer to achieve online gain adjustment.At the same time,an adaptive high frequency signal injection method is proposed to solve the problem that the nonlinear flux observer is limited by the fixed gain value and the stability is poor at low speed.Finally,a simulation model is built in MATLAB environment to verify the proposed algorithm,and the simulation results show that the position error of the new observer is reduced by more than 37.5%,the convergence speed is increased by more than 50%,and the system chattering is effectively suppressed with stronger robustness.
作者
赵化勇
田伟
吉敬华
ZHAO Huayong;TIAN Wei;JI Jinghua(School of Electrical and Information Engineering,Jiangsu University,Zhenjiang 212013,China)
出处
《组合机床与自动化加工技术》
北大核心
2025年第4期129-132,139,共5页
Modular Machine Tool & Automatic Manufacturing Technique
关键词
双三相永磁同步电机
矢量控制
离散型非线性磁链观测器
BP神经网络
高频信号注入
dual three-phase permanent magnet synchronous motor
vector control
discrete nonlinear flux observer
BP neural network
high frequency signal injection
