非局部迟滞函数辨识与补偿的神经网络

P. Berényi, G. Horváth
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引用次数: 0

摘要

讨论了在机械摩擦、磁性材料和压电作动器中遇到的非局部静态滞回函数的在线辨识,并通过控制器的设计引起问题。提出了一种基于简化鲁汶摩擦模型和借鉴神经网络技术的预滑动摩擦补偿方法。我们提出了一种如何识别由摩擦引起的迟滞以及如何使用该识别模型来补偿摩擦效应的解决方案。给出了仿真和实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural networks for nonlocal hysteresis function identification and compensation
We discuss the online identification of nonlocal static hysteresis functions, which are encountered in mechanical friction, magnetic materials, and piezoelectric actuators and causes problems by the design of controllers. We introduce a compensation method for friction in presliding regime based on the simplified Leuven friction model and on technology borrowed from neural networks. We present a solution how to identify the hysteresis caused by the friction and how to use this identified model for the compensation of the friction effects. Results from both simulations and experiments are shown.
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