无传感器永磁同步电机驱动的无气味卡尔曼滤波干扰估计

Dariusz Janiszewski
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引用次数: 4

摘要

本文对永磁同步电机无传感器控制在机电一体化中的应用进行了研究和实验验证。提出了一种新的基于Unscented卡尔曼滤波的估计策略,仅利用电机电流的测量来在线估计转速、转子位置和扰动负载转矩。对于像机械臂这样复杂的驱动控制系统,负载信息是非常重要的。特别是在无传感器系统中,很少采用估计的方法来获得。常用卡尔曼滤波器是一种最优状态估计器,通常用于包含随机噪声环境的动态系统。控制结构采用无气味算法,在实时性上需要非常高效的信号处理器。实验结果验证了该估计方法的有效性和适用性。
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Disturbance estimation for sensorless PMSM drive with Unscented Kalman Filter
This paper describes a study and experimental verification of sensorless control of Permanent Magnet Synchronous Motor in mechatronics application. There are proposed novel estimation strategy based on the Unscented Kalman Filter, using only the measurement of the motor current for on-line estimation of speed, rotor position and disturbance - load torque. Information about the load is important for complex drive control systems like robot arm. It is seldom obtained by estimation way especially in sensorless systems. Used Kalman filter is an optimal state estimator and is usually applied to a dynamic system that involves a random noise environment. Control structure with unscented algorithm, in real time requires a very efficient signal processor. Experimental results have been carried out to verify the effectiveness and applicability of the novel proposed estimation technique.
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