首页> 外文会议>2010 IEEE International Conference on Power and Energy >On-line parameter estimation of an induction machine using a recursive least-squares algorithm with multiple time-varying forgetting factors
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On-line parameter estimation of an induction machine using a recursive least-squares algorithm with multiple time-varying forgetting factors

机译:使用具有多个时变遗忘因子的递归最小二乘算法对感应电机进行在线参数估计

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This paper proposes a recursive least-squares (RLS) algorithm with multiple time-varying forgetting factors for on-line parameter estimation of an induction machine (IM). The regressive mathematical model of the IM is also introduced which is simple and appropriate for online parameter estimation. The estimator inputs using the proposed RLS algorithm are easily measurable variables such as the stator voltages and currents as well as the rotor speed of the IM. The simulation results obtained compare the estimated parameters with the IM parameters achieved using other RLS algorithms such as a standard RLS algorithm and a RLS with a constant forgetting factor. The comparison shows that the proposed RLS algorithm is better than others for on-line parameter estimation of the IM.
机译:本文提出了一种具有多个时变遗忘因子的递归最小二乘(RLS)算法,用于感应电机(IM)的在线参数估计。还介绍了IM的回归数学模型,该模型简单且适用于在线参数估计。使用提出的RLS算法的估算器输入是易于测量的变量,例如IM的定子电压和电流以及转子速度。获得的仿真结果将估计的参数与使用其他RLS算法(例如标准RLS算法和具有恒定遗忘因子的RLS)获得的IM参数进行比较。比较表明,所提出的RLS算法在IM的在线参数估计方面优于其他算法。

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