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Improved Iterative Learning Direct Torque Control for Torque Ripple Minimization of Surface-Mounted Permanent Magnet Synchronous Motor Drives

机译:改进的迭代学习直接扭矩控制,用于扭矩脉动最小化表面安装的永磁同步电动机驱动器

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This article presents an improved iterative learning direct torque control (IL-DTC) to remarkably minimize the torque ripples for a surface-mounted permanent magnet synchronous motor (SPMSM) drive. Unlike the conventional IL-DTC, the proposed IL-DTC significantly attenuates the torque ripples by effectively suppressing the repetitive disturbances using the speed and load torque compensating terms in the improved error dynamics via the improved feedback control terms and iterative learning control terms. Further, it has a simple structure and fast dynamic response due to the direct control of the torque and flux. The stability is verified through the convergence of speed errors to zero as the iteration index goes to infinity. The comparative results via MATLAB/Simulink and a prototype SPMSM test-bed with TI-TMS320F28335-DSP demonstrate the improved control performance (e.g., less torque ripples, faster transient response, smaller overshoot/undershoot, and smaller steady-state error) over the conventional IL-DTC under critical load/speed conditions with severe model parameter uncertainties.
机译:本文介绍了一种改进的迭代学习直接扭矩控制(IL-DTC),以显着最小化用于表面安装的永磁同步电动机(SPMSM)驱动器的扭矩纹波。与传统的IL-DTC不同,所提出的IL-DTC通过通过改进的反馈控制术语和迭代学习控制术语有效地抑制改进的误差动态中的速度和负载扭矩补偿术语来显着抑制转矩涟漪。此外,由于对扭矩和通量的直接控制,它具有简单的结构和快速动态响应。随着迭代索引转到无穷大,通过速度误差的汇聚来验证稳定性。通过MATLAB / SIMULINK的比较结果和具有TI-TMS320F28335-DSP的原型SPMSM TEST-BOIT展示了改进的控制性能(例如,扭矩涟漪,更快的瞬态响应,较小的瞬态响应,较小的过冲/下冲和较小的稳态误差)。常规IL-DTC在具有严重模型参数不确定性的临界负载/速度条件下。

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