一种改进的五相永磁同步电机无差拍预测电流控制

Tianxing Li, Ruiqing Ma
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引用次数: 1

摘要

无差拍预测电流控制(DPCC)具有许多优点,但其控制效果高度依赖于数学模型和参数匹配程度。随着速度的增加,传统欧拉离散方法得到的离散模型与连续模型之间的误差也会增大。此外,由系统延迟引起的一步延迟控制也会影响DPCC控制效果。为了提高DPCC的控制性能和对参数扰动的鲁棒性,本文对传统的DPCC进行了优化。首先,基于欧拉离散方法,给出了改进的预测模型,以减小离散化带来的误差,并分析了参数扰动对改进预测模型的影响。其次,根据电流预测值、参考值和输出电压矢量得到系统的延时时间;然后,根据延迟时间补偿下一拍最优电压矢量。最后,提出了一种基于变增益超扭转算法(VA-STA)的二阶滑模观测器,实现了参数误差的观测,并以前馈观测的形式对DPCC输出结果进行了补偿。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improved Deadbeat Predictive Current Control for Five-Phase PMSM
Deadbeat Predictive Current Control (DPCC) has many advantages, but its control effect is highly dependent on the mathematical model and parameter matching degree. As the speed increases, the error between the discrete model obtained by the traditional Euler discrete method and the continuous model will also increase. Besides, the one-step delay control caused by the system delay will also affect the DPCC control effect. In order to improve the control performance of DPCC and the robustness of parameter disturbance, this paper optimizes the traditional DPCC. Firstly, based on the Euler discrete method, the improved prediction model is given to reduce the error caused by discretization, and the influence of parameter disturbance on the improved prediction model is analyzed. Secondly, the system's delay time is obtained according to the current prediction value, reference value, and output voltage vector. And then, the next beat optimal voltage vector is compensated according to the delay time. Finally, a second-order sliding mode observer based on the variable-gain super-twisting algorithm(VA-STA) is proposed, which realizes the observation of parameter errors and compensates the DPCC output results in the form of feed-forward observations.
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