Adaptive self-tuning MTPA vector controller for IPMSM drive system
Adaptive self-tuning MTPA vector controller for IPMSM drive system
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DOI：
10.1109/tec.2006.878243
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发表时间：
2006-08
影响因子：
4.9
通讯作者：
Yasser Abdel-Rady Ibrahim Mohamed;Tsing K. Lee
中科院分区：
文献类型：
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作者：
Yasser Abdel-Rady Ibrahim Mohamed;Tsing K. Lee
提出了一种内部永磁同步电机驱动系统的自适应自整定最大转矩/安培矢量控制器。该控制方案由同步帧解耦电流控制器、MTPA转矩控制器和自适应参数估计器组成。该估计器应用于q轴电流动态，因为d轴电感可以假定为恒定而不损失精度。由于q轴电流动态受到磁体反电动势电压的干扰，所提出的估计器与鲁棒主动状态解耦方案相结合，以确保参数估计无偏。采用基于最陡下降法的简单自适应算法估计磁体的磁链，实现了鲁棒解耦方案。将鲁棒解耦方案与q轴电流动力学相结合，大大简化了系统模型。在简化模型的基础上，采用自然自适应观测器估计q轴电流。利用仿射投影提供的迭代梯度算法，通过最小化状态估计误差来估计未知电机参数。将估计的参数用于自整定控制。实验结果证明了在线参数估计和控制环整定技术的有效性和实用性
This paper presents an adaptive self-tuning maximum torque per ampere (MTPA) vector controller for an interior permanent-magnet synchronous motor (IPMSM) drive system. The control scheme consists of a synchronous frame decoupling current controller, MTPA torque controller, and adaptive parameter estimator. The estimator is applied to the q-axis current dynamics as the d-axis inductance can be assumed to be constant without loss of accuracy. Since the q-axis current dynamics is being disturbed by the magnet's back-EMF voltage, the proposed estimator is combined with a robust active-state decoupling scheme to ensure unbiased parameter estimate. The robust decoupling scheme is realized by estimating the magnet's flux linkage by a simple adaptation algorithm based on the steepest descent method. The system's model is greatly simplified when the robust decoupling scheme is combined with the q-axis current dynamics. Relying on the simplified model, a natural adaptive observer is used to estimate the q-axis current. Unknown motor parameters are estimated by minimizing the state estimation error using an iterative gradient algorithm offered by the affine projection. The estimated parameters are used for the self-tuning control. Experimental results are presented to demonstrate the validity and usefulness of the online parameter estimation and control loop tuning technique