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A Cross-Coupled Iterative Learning Control Design for Biaxial Systems Based on Natural Local Approximation of Contour Error

机译:基于轮廓误差自然局部近似的双轴系统交叉耦合迭代学习控制设计

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摘要

The contour error is the core index to measure the machining quality, so how to get an accurate contour error value and reduce contour error is still an urgent problem in the production process, especially in high-speed and large-curvature contouring tasks. In this paper, a cross-coupled iterative learning control (CCILC) based on natural local approximation of contour error is proposed to reduce the contour error in the repetitive machining process. Simulations and experiments on XY-table demonstrate that the contour error can be reduced effectively by using the proposed method.
机译:轮廓误差是测量加工质量的核心索引,因此如何获得准确的轮廓误差值并降低轮廓错误仍然是生产过程中的迫切问题,特别是在高速和大曲率的轮廓任务中。在本文中,提出了一种基于轮廓误差的自然局部近似的交叉耦合迭代学习控制(CCILC),以减少重复加工过程中的轮廓误差。 XY表的模拟和实验表明,通过使用所提出的方法可以有效地减少轮廓误差。

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