Continuous-Control-Set Model Predictive Control with Integrated Modulator in Permanent Magnet Synchronous Motor Applications
Continuous-Control-Set Model Predictive Control with Integrated Modulator in Permanent Magnet Synchronous Motor Applications
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DOI：
10.1109/iemdc.2019.8785122
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发表时间：
2019-05
期刊：
影响因子：
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通讯作者：
Sören Hanke;Oliver Wallscheid;J. Böcker
中科院分区：
文献类型：
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作者：
Sören Hanke;Oliver Wallscheid;J. Böcker
电驱动控制的一个关键方面是对高控制性能的需求。除了短的建立时间和小的设定点偏差外，还需要低电流涟漪。不可避免的涟漪是由所使用的电压源逆变器的开关原理引起的。在确定驱动变量时对涟漪的考虑在已建立的控制方法之间是不同的，例如磁场定向控制（FOC）、有限控制集（FCS）或连续控制集（CCS）模型预测控制（MPC）。这也取决于是否使用专用调制器。提出了一种集成调制器的CCS-MPC，在优化过程中考虑了类脉宽调制（PWM）的原理。设定点偏差和电流涟漪是优化问题的目标。在这里，选择一个适当的成本函数进行调查，使得在稳态的性能是可比的FOC和瞬态过程中的MPC方法。所选择的成本函数还定义了在每个控制器周期中要在线求解的优化问题的类别。除了仿真研究，实验装置与永磁同步电动机（PMSM）和qpOASES作为求解器的实时优化。
A key aspect in the control of electrical drives is the demand for a high control performance. In addition to a short settling time and a small setpoint deviation, a low current ripple is desired. The unavoidable ripple is caused by the switching principle of the used voltage-source inverters. The consideration of the ripple when determining the actuating variables differs between the established control approaches such as the field-oriented control (FOC), the finite-control-set (FCS), or the continuous-control-set (CCS)model predictive control (MPC). This also depends on whether a dedicated modulator is used or not. A CCS-MPC with integrated modulator which takes the principle of a pulse width modulation-like modulator (PWM)during optimization into account is presented. The setpoint deviation and the current ripple are the objectives of a optimization problem. Here, choosing an appropriate cost function is investigated such that the performance in steady state is comparable to that of a FOC and during transients to that of a MPC approach. The chosen cost function also defines the class of the optimization problem to be solved online in each controller cycle. Besides a simulative investigation, an experimental setup with a permanent magnet synchronous motor (PMSM)and qpOASES as solver for real-time optimizations was implemented.