We propose an optimization-based method to improve contour tracking performance on precision motion stages by modifying the reference trajectory, without changing the built-in low-level controller. The position of the precision motion stage is predicted with data-driven models. First, a linear low-fidelity model is used to optimize traversal time, by changing the path velocity and acceleration profiles. Second, a non-linear high-fidelity model is used to refine the previously found time-optimal solution. We experimentally demonstrate that the method is capable of improving the productivity vs. accuracy trade-off for a high precision motion stage. Given the data-based nature of the models used, we claim that the method can easily be adapted to a wide family of precision motion systems.
翻译:我们建议一种基于优化的方法,通过修改参考轨迹来改进精确运动阶段的轮廓跟踪性能,同时不改变内置低级控制器。精确运动阶段的位置是用数据驱动模型预测的。首先,使用线性低纤维化模型来通过改变路径速度和加速度剖面来优化穿梭时间。第二,使用非线性高不洁模型来完善以前找到的时间最优解决方案。我们实验性地证明,该方法能够提高生产率,相对于精密运动阶段的精度取舍。鉴于所使用模型的数据性质,我们声称,该方法很容易适应广泛的精密运动系统。