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Adaptive fuzzy self-learning controller based rotor resistance estimator for vector controlled induction motor drive

机译:基于自适应模糊自学习控制器的矢量感应电动机驱动器转子电阻估计器

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摘要

This paper presents an intelligent approach to identify and adapt the rotor resistance for an indirect vector controlled induction motor drive. This command is affected by rotor resistance; the variation of this parameter could distort the decoupling between flux and torque and, consequently, lead to deterioration of drive performance. To overcome this problem, a fuzzy estimator is provided to identify the real value of rotor resistance in order to obtain a vector control optimal. Then we propose a fuzzy adaptive control strategy fits into the learning methods context by modifying the consequences of fuzzy estimator. Regarding the learning algorithm, our solution envisages the use of a fuzzy inverse model, combined with a mechanism that acts based on estimator rules by modifying the consequents according to a certain criterion, so as to increase the system robustness, and avoid unnecessary oscillation in the control signal. The suggested rotor resistance identification approach has been validated by simulation study.
机译:本文提出了一种智能方法来识别和适应间接矢量控制感应电动机驱动器的转子电阻。该命令受转子电阻的影响。该参数的变化可能会使磁通和转矩之间的解耦失真,从而导致驱动性能下降。为了克服这个问题,提供了模糊估计器以识别转子电阻的真实值,以获得最优的矢量控制。然后,通过修改模糊估计量的结果,提出一种适合学习方法环境的模糊自适应控制策略。关于学习算法,我们的解决方案设想使用模糊逆模型,并结合一种机制,该机制根据估计器规则通过根据特定准则修改结果来发挥作用,从而提高系统的鲁棒性,并避免系统中不必要的振荡。控制信号。建议的转子电阻识别方法已经通过仿真研究得到验证。

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