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首页> 外文期刊>ISA Transactions >Cogging effect minimization in PMSM position servo system using dual high-order periodic adaptive learning compensation
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Cogging effect minimization in PMSM position servo system using dual high-order periodic adaptive learning compensation

机译:使用双高阶周期性自适应学习补偿的PMSM位置伺服系统中的齿槽效应最小化

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摘要

Cogging effect which can be treated as a type of position-dependent periodic disturbance, is a serious disadvantage of the permanent magnetic synchronous motor (PMSM). In this paper, based on a simulation system model of PMSM position servo control, the cogging force, viscous friction, and applied load in the real PMSM control system are considered and presented. A dual high-order periodic adaptive learning compensation (DHO-PALC) method is proposed to minimize the cogging effect on the PMSM position and velocity servo system. In this DHO-PALC scheme, more than one previous periods stored information of both the composite tracking error and the estimate of the cogging force is used for the control law updating. Asymptotical stability proof with the proposed DHO-PALC scheme is presented. Simulation is implemented on the PMSM servo system model to illustrate the proposed method. When the constant speed reference is applied, the DHO-PALC can achieve a faster learning convergence speed than the first-order periodic adaptive learning compensation (FO-PALC). Moreover, when the designed reference signal changes periodically, the proposed DHO-PALC can obtain not only faster convergence speed, but also much smaller final error bound than the FO-PALC.
机译:齿槽效应可以看作是一种位置相关的周期性干扰,是永磁同步电动机(PMSM)的严重缺点。本文基于永磁同步电机位置伺服控制的仿真系统模型,考虑并提出了实际永磁同步电机控制系统中的齿槽力,粘滞摩擦以及所施加的载荷。提出了一种双高阶周期性自适应学习补偿(DHO-PALC)方法,以减小对永磁同步电机位置和速度伺服系统的齿槽效应。在该DHO-PALC方案中,存储了复合跟踪误差和齿槽效应的估计两者的信息的一个以上的先前周期用于控制律更新。提出了所提出的DHO-PALC方案的渐近稳定性证明。在PMSM伺服系统模型上进行了仿真,以说明所提出的方法。当应用恒定速度参考时,DHO-PALC可以获得比一阶周期性自适应学习补偿(FO-PALC)更快的学习收敛速度。此外,当设计的参考信号周期性变化时,与FO-PALC相比,提出的DHO-PALC不仅可以获得更快的收敛速度,而且最终误差范围也小得多。

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