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首页> 外文期刊>IEEE Transactions on Industrial Electronics >High-Precision Control of Ball-Screw-Driven Stage Based on Repetitive Control Using -Times Learning Filter
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High-Precision Control of Ball-Screw-Driven Stage Based on Repetitive Control Using -Times Learning Filter

机译：基于-Times学习滤波器的重复控制的高精度滚珠丝杠驱动级控制

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摘要

This paper presents a novel learning control method for ball-screw-driven stages. In recent years, many types of friction models that are based on complicated equations have been studied. However, it is difficult to treat friction models with equations because the level of precision that is associated with real friction characteristics and parameter tuning are difficult to achieve. In contrast, repetitive perfect tracking control (RPTC) is a repetitive control technique that achieves high-precision positioning. In this paper, we propose the use of RPTC with $n$-times learning filter. The $n$-times learning filter has a sharper rolloff property than conventional learning filters. With the use of the $n$-times learning filter, the proposed RPTC can converge tracking errors $n$ times faster than the RPTC with the conventional learning filter. Simulations and experiments with a ball-screw-driven stage show the fast convergence of the proposed RPTC. Finally, the proposed learning control scheme is combined with data-based friction compensation, and the effectiveness of this combination is verified for the $x$ –$y$ stage of a numerically controlled machine tool.
机译：本文提出了一种用于滚珠丝杠驱动平台的新型学习控制方法。近年来，已经研究了许多基于复杂方程式的摩擦模型。但是，很难用方程式来处理摩擦模型，因为与实际摩擦特性和参数调整相关的精度水平很难达到。相反，重复式完美跟踪控制（RPTC）是实现高精度定位的重复式控制技术。在本文中，我们建议使用带$ n $次学习过滤器的RPTC。 $ n $倍的学习过滤器具有比常规学习过滤器更陡峭的滚降特性。通过使用$ n $倍的学习滤波器，所提出的RPTC可以比使用传统学习滤波器的RPTC更快地收敛跟踪误差$ n $倍。滚珠丝杠驱动平台的仿真和实验表明了所提出的RPTC的快速收敛。最后，将提出的学习控制方案与基于数据的摩擦补偿相结合，并在数控机床的$ x $ – $ y $阶段验证了这种组合的有效性。

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