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Speed-Sensorless Finite Control Set Model Predictive Control of PMSM with Permanent Magnet Flux Linkage Estimation

机译:永磁磁链估计的永磁同步电机无速度传感器有限控制模型预测控制

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Permanent magnet synchronous motors (PMSMs) have become the focus of interest in electrical machine drive systems due to their advantages. These motors can have a nonlinear model with time-varying parameters, making them difficult to control. Therefore, model predictive control (MPC) is inherently very suitable to control PMSMs due to the inclusion of nonlinearities and constraints. Also, the elimination of speed-sensors reduces cost and hardware-complexity. Furthermore, the estimation of time-varying parameters also improves control performance. Therefore, in this paper, a speed-sensorless MPC for a PMSM based on an adaptive fading extended Kalman filter is considered. The proposed drive system is robust to changes in load-torque and permanent magnet flux linkage. As a result, a good estimation performance has been achieved.
机译:永磁同步电动机(PMSM)由于其优点已经成为电机驱动系统中的关注焦点。这些电动机可能具有带有时变参数的非线性模型,从而使其难以控制。因此,由于包含了非线性和约束条件,模型预测控制(MPC)本质上非常适合于控制PMSM。而且,消除速度传感器降低了成本和硬件复杂性。此外,时变参数的估计也提高了控制性能。因此,在本文中,考虑了基于自适应衰落扩展卡尔曼滤波器的PMSM无速度传感器MPC。所提出的驱动系统对于改变负载转矩和永磁通量链具有鲁棒性。结果,获得了良好的估计性能。

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