摘要
为了提高永磁同步电机电流增量预测控制策略的参数自适应性,提出一种基于增量式模型参考自适应的电感在线辨识算法。该算法使用永磁同步电机的增量模式的电压方程作为可调模型,以实际电机作为参考模型,建立基于模型参考自适应的参数辨识机制,在线辨识交直轴电感;通过判断激励信号的有效性去除噪声等非理想因素的影响,消除辨识结果的稳态波动。研究结果表明,所提出的增量式模型参考自适应算法可以辨识出准确的电感参数,避免辨识结果的频繁波动,显著提高增量预测控制策略对模型参数的自适应性,同时计算量少,对电机参数依赖度低。仿真和实验结果验证了所提方案的有效性。
Aiming at increasing robustness to parameter mismatch of incremental predictive current control method for permanent magnet synchronous motor （PMSM）, an online identification algorithm of induct-ance based on incremental mode of model reference adaptive system （MRAS） is proposed. The incre-mental mode of voltage equation of PMSM was treated as an adjustable model, while the actual motor was as a reference model. In this way, parameter identification mechanism according to MRAS was estab-lished to identify inductance online. In addition, adverse effect from non-ideality factors, e. g. , system noise, was eliminated by judging validity of the stimulus signal, thus reducing frequent fluctuation of the identification result. Research shows that the proposed algorithm can obtain accurate inductance of the controlled motor and avoid frequent fluctuations in the identified result, leading to significant improve-ment of robustness to parameter mismatch of incremental predictive current control method. Besides, it has the advantages of a little calculation burden required and low dependence on motor parameters. Simu-lation and experimental results verify the effectiveness of the proposed scheme.
出处
《电机与控制学报》
EI
CSCD
北大核心
2014年第2期75-82,共8页
Electric Machines and Control
基金
国家自然科学基金(51177084)
关键词
模型参考自适应
增量预测控制
永磁同步电机
带宽
model reference adaptive system
incremental predictive control
permanent magnet synchro-nous motors
bandwidth
