The finite control set model predictive current control involves addressing challenges related to greater cost function values and inaccurate current prediction models, which can adversely impact the steady-state performance in permanent magnet synchronous motor (PMSM). A robust amplitude control set model predictive current control method (RACSMPCC) is proposed in this study, aiming to enhance prediction accuracy and control precision. This method introduces a rotation coordinate system amplitude control set to reduce the cost function value and improve current control precision. Then, a nonlinear extended state observer (NESO) is employed to observe and compensate for comprehensive disturbances in the current prediction equation, thereby improving the accuracy of the current prediction. Simultaneously, a parameter configuration method in the complex frequency domain is proposed for NESO, and its influence on the disturbance rejection performance of the system is analyzed. Hardware experiments on a PMSM are conducted to validate the effectiveness of RACSMPCC in reducing cost function and improving current control accuracy.

中文翻译：

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基于非线性扩展状态观测器的SPMSM低成本误差鲁棒幅度控制集模型预测控制

有限控制集模型预测电流控制涉及解决与较大成本函数值和不准确的电流预测模型相关的挑战，这可能对永磁同步电机 (PMSM) 的稳态性能产生不利影响。本文提出了一种鲁棒幅度控制集模型预测电流控制方法（RACSMPCC），旨在提高预测精度和控制精度。该方法引入旋转坐标系振幅控制集来降低成本函数值，提高电流控制精度。然后，采用非线性扩展状态观测器（NESO）对当前预测方程中的综合扰动进行观测和补偿，从而提高当前预测的精度。同时，提出了NESO的复频域参数配置方法，并分析了其对系统抗扰性能的影响。在 PMSM 上进行硬件实验，验证 RACSMPCC 在降低成本函数和提高电流控制精度方面的有效性。