Trajectory extension methods for model predictive direct torque control
Trajectory extension methods for model predictive direct torque control
复制标题
模型预测直接扭矩控制的轨迹扩展方法
DOI：
10.1109/apec.2011.5744819
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
B. Egardt
中科院分区：
文献类型：
--
作者：
Yashar Zeinaly;T. Geyer;B. Egardt
本文研究的是模型预测直接转矩控制(MPDTC)，它是一种结合了模型预测控制(MPC)和直接转矩控制(DTC)思想的新型三相交流电机控制方案。利用驱动器的动态模型，MPDTC预测未来的几个开关转换，扩展输出，并选择最小开关频率或开关损耗的逆变器开关位置。MPDTC的性能取决于预测的准确性。然而，具有非常准确预测的MPTDC方案在计算上要求非常快的控制器硬件。提出了扩展输出轨迹的新方法，从而产生快速而准确的预测，从而产生计算高效的MPDTC方案。从计算复杂度和预测精度两个方面说明了所提方法的优越性。
This paper focuses on model predictive direct torque control (MPDTC), which is a recent control scheme for three-phase ac electric drives combining the notions of model predictive control (MPC) and direct torque control (DTC). Using a dynamic model of the drive, MPDTC predicts several future switch transitions, extends the outputs and chooses the inverter switch positions that minimize the switching frequency or the switching losses. The performance of MPDTC depends on the accuracy of the predictions. However, MPTDC schemes with very accurate predictions are computationally demanding necessitating very fast controller hardware. New methods for extending the output trajectories are proposed that yield fast yet accurate predictions giving rise to a computationally efficient MPDTC scheme. The advantages of the proposed methods are shown in terms of the associated computational complexity and the accuracy of the predictions.