摘要
针对应用于盾构主驱动的感应电机无速度传感器矢量控制系统,传统模型参考自适应系统(model reference adaptive system,MRAS)中的比例积分(proportional integral,PI)自适应率需要人工经验调整,且不能够根据模型变化而变化的问题,提出了一种新的预测MRAS速度估计器,用于无传感器感应电机(induction machine,IM)驱动。该估计器基于有限控制集模型预测控制原理。转子转速的计算采用基于搜索的优化算法,保证了在每个采样周期转速调整误差信号最小,避免了使用比例积分控制器。实验结果表明,所提速度估计器在较宽的速度范围内都具有良好的动静态性能。
A new predictive model reference adaptive system(MRAS)speed estimator was proposed to address the problem of the traditional proportional-integral(PI)adaptive rate in the induction machine(IM)drive system used for shield tunneling without a speed sensor.The traditional PI adaptive rate in the MRAS system relies on manual experience adjustment and cannot adapt to model changes.The proposed estimator was based on the principles of finite control set model predictive control.A search-based optimization algorithm was adopted during the rotor speed calculation,which ensures minimum speed adjustment error signals in each sampling period and avoids the use of a proportional integral controller.Experimental results show that the proposed speed estimator has excellent dynamic and static performance over a wide speed range.
作者
安小宇
梅永祥
郭磊磊
贾连辉
孙志洪
任成龙
王浩宇
AN Xiao-yu;MEI Yong-xiang;GUO Lei-lei;JIA Lian-hui;SUN Zhi-hong;REN Cheng-long;WANG Hao-yu(College of Electrical and Information Engineering,Zhengzhou University of Light Industry,Zhengzhou 450002,China;China Railway Engineering Equipment Group Co.,Ltd.,Zhengzhou 450016,China)
出处
《科学技术与工程》
北大核心
2024年第25期10783-10789,共7页
Science Technology and Engineering
基金
国家自然科学基金(51707176)。
关键词
感应电机
矢量控制
模型预测控制
模型自适应
无传感器控制
induction machine
vector control
model predictive control
model adaptive
sensorless control
