IPMSM模型预测控制中的电压利用

Michael Leuer, J. Bocker
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引用次数: 2

摘要

模型预测控制(MPC)包括被控系统的数学模型。基于该模型,在每个采样步中确定未来时间步的最优驱动变量。因此,与传统控制相比,MPC对设定值步长表现出更好的响应。针对具有固有输出饱和的非线性系统,提出了一种模型预测控制方法。这种方法为在线MPC提供了实时能力,即使过程时间常数在毫秒范围内,也可以使用MPC控制带内磁铁的永磁同步电机(IPMSM)。除了良好的动力学外,直流链路电压的利用对这些电机类型很重要。由于MPC能够最佳地利用可用的直流链路电压,因此MPC不仅在动态方面优于传统控制。仿真结果和试验台的测量结果都证明了这一点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Voltage utilization in Model Predictive Control for IPMSM
Model Predictive Control (MPC) includes a mathematical model of the controlled system. Based on this model optimal actuating variables for future timesteps are determined in every sampling step. Thus the MPC exhibits a better response to a setpoint step compared to conventional control. In this paper a Model Predictive Control method for nonlinear systems with inherent output saturation is presented. This approach offers real-time capability for online MPC even with process time constants in the range of milliseconds, enabling the use of MPC for control of permanent magnet synchronous motors with interior magnets (IPMSM). Besides the good dynamics, the utilization of the DC link voltage is important for these motor types. Since the MPC is able to utilize the available DC link voltage optimally, the MPC is superior to conventional controls not only in terms of dynamics. This is demonstrated by simulation results, as well as by measurements on a testbench.
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