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Online fuzzy tuning of weighting factor in model predictive control of PMSM

机译:PMSM模型预测控制加权因子的在线模糊调整

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Permanent magnet synchronous motors (PMSMs) have sensible characteristics which make them attractive in industrial applications such as high power density, high efficiency and high torque. Hence they are suitable for a wide variety of applications, especially where weight and size are restricted. Several methods have been proposed to control PMSMs such as field oriented control (FOC) and direct torque control (DTC). Utilization of the PWM and a PI as a current controller is the common feature in the mentioned methods, while the model predictive control (MPC) generates the switching signals directly by optimization of a cost function and as will be explained, doesn't use a PI to control the motor currents. In this paper a fuzzy procedure is applied to tune the weighting factor of the cost function online as the reference changes. Because the weighting factor affects the torque ripple and currents ripple and should be changed to obtain the best performance during the variation of reference. A program in matlab has been developed to verify the efficiency of the method. The results are demonstrated and compared in the following sections.
机译:永磁同步电动机(PMSMS)具有明智的特性,使其在高功率密度,高效率和高扭矩等工业应用中具有吸引力。因此,它们适用于各种各样的应用,尤其是在重量和尺寸受到限制的情况下。已经提出了几种方法来控制PMSM,例如现场取向控制(FOC)和直接扭矩控制(DTC)。作为当前控制器的PWM和PI的利用是所提到的方法中的公共特征,而模型预测控制(MPC)通过优化成本函数直接生成切换信号,并且如将解释,不使用a PI控制电机电流。在本文中,应用了模糊程序来调整在线成本函数的加权因子作为参考变化。因为加权因子影响扭矩纹波和电流纹波,并且应该改变以获得在参考的变化期间获得最佳性能。已经开发了MATLAB中的程序以验证该方法的效率。结果在以下部分进行了证明和比较。

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