A Current Control Scheme With an Adaptive Internal Model for Torque Ripple Minimization and Robust Current Regulation in PMSM Drive Systems
A Current Control Scheme With an Adaptive Internal Model for Torque Ripple Minimization and Robust Current Regulation in PMSM Drive Systems
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DOI：
10.1109/tec.2007.914352
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发表时间：
2008-02
影响因子：
4.9
通讯作者：
Y. Mohamed;Ehab F. El-Saadany
中科院分区：
文献类型：
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作者：
Y. Mohamed;Ehab F. El-Saadany
针对实际永磁同步电机的不确定性问题，提出了一种简单的电流反馈和参考电流产生结构中的自适应内部模型作为解决方案。针对实际永磁同步电机驱动系统中不确定性的时变性和高带宽特性，简单地选择内部模型作为估计的不确定性函数。为了提供具有高抗噪性的不确定函数的高带宽估计，利用标称电流动态，在Lyapunov函数意义下推导了一种简单的自适应律。在稳定的闭环系统中加入了需要消除的扰动的频率模式(由参数变化引起的磁链谐波和电压扰动)，在对应于不确定模式的不同频率模式下引入了非常高的衰减。因此，获得了稳健的转矩脉动最小化和电流调节性能。为了适当地调整所提出的方案，基于离散时间Lyapunov函数的稳定性分析被用来确定自适应增益的稳定极限。仿真结果表明，所提出的控制方案在不同的运行条件下是有效的。
This paper addresses the problem of uncertainties in practical permanent magnet synchronous motors (PMSMs), and proposes a simple adaptive internal model within the current feedback and reference current generation structure as a solution. Due to the time varying nature and the high-bandwidth property of uncertainties in a practical PMSM drive system, the internal model is simply chosen as the estimated uncertainty function. To provide a high bandwidth estimate of the uncertainty function with high-noise immunity, a simple adaptation law is derived, in the sense of Lyapunov functions, using the nominal current dynamics. The inclusion of the frequency modes of the disturbances to be eliminated (the flux harmonics and voltage disturbances caused by parameter variation) in the stable closed-loop system introduces very high-attenuation at different frequency modes corresponding to uncertainty modes. Therefore, a robust torque ripple minimization and current regulation performances are yielded. To properly tune the proposed scheme, a stability analysis based on a discrete-time Lyapunov function has been used to determine the stability limits of the adaptation gain. Comparative evaluation results are presented to demonstrate the effectiveness of the proposed control scheme under different operating conditions.