High-performance motion control of an XY stage for complicated contours with BFC trajectory planning

Abstract

To meet the requirements of contouring accuracy, multi-axis coordination, and high productivity in the fields of machining tools, many researchers devote to exploring various strategies in terms of controller design, coordinate frame construction, and trajectory planning for high-performance multi-axis motion. In this paper, a generalized global task coordinate frame (GTCF) is constructed for complicated contours to make the calculation of contouring error equal to the first-order approximation of the actual contouring error at any position in the GTCF no matter how large the tracking error or contour curvature would be, which suggests that the contouring error of complicated curves can be directly controlled in the GTCF. Furthermore, an experimental investigation is conducted over an XY linear-motor-driven stage on the combination of a GTCF based learning adaptive robust controller (LARC) with a back and forward check (BFC) algorithm. The LARC scheme is designed in a serial structure of an adaptive robust control (ARC) term and an iterative learning control (ILC) term, which guarantees good parametric adaptation and excellent contouring accuracy. In addition, the BFC algorithm provides an efficient computation for minimum time feed-rate optimization. A Lissajous curve and flower-shape curves are used as case studies to demonstrate the efficacy of the generalized GTCF based LARC scheme with BFC. The proposed GTCF-LARC-BFC approach provides a high-performance and efficient contouring control framework as a guidance for applications in motion control on industrial XY systems such as precision laser engravers.