Data-driven Reference Trajectory Optimization for Precision Motion Systems
We propose a data-driven optimization-based pre-compensation method to improve the contour tracking performance of precision motion stages by modifying the reference trajectory and without modifying any built-in low-level controllers. The position of the precision motion stage is predicted with data...
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Zusammenfassung: | We propose a data-driven optimization-based pre-compensation method to
improve the contour tracking performance of precision motion stages by
modifying the reference trajectory and without modifying any built-in low-level
controllers. The position of the precision motion stage is predicted with
data-driven models, a linear low-fidelity model is used to optimize traversal
time, by changing the path velocity and acceleration profiles then a non-linear
high-fidelity model is used to refine the previously found time-optimal
solution. We experimentally demonstrate that the proposed method is capable of
simultaneously improving the productivity and accuracy of a high precision
motion stage. Given the data-based nature of the models, the proposed method
can easily be adapted to a wide family of precision motion systems. |
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DOI: | 10.48550/arxiv.2205.15694 |