Embedded iterative learning contouring controller design for biaxial feed drive systems

Abstract

In machine tool control, not only tracking errors in each drive axis but also contour errors, which is directly related to the machined shape of workpiece, should be considered. Although most existing contouring controllers are based on feedback control, this paper proposes an embedded iterative learning contouring controller (EILCC) by considering both tracking and contour errors. The reference trajectory of each feed drive axis is iteratively modified to increase the tracking performance by which contour error converges fast within a few iterations. The proposed controller can be directly applied to commercial machines currently in use without detail knowledge of their controllers or actual system parameters. The proposed method has been simulated on a sharp-corner trajectory which normally leads to large contour errors around the corner due to its discontinuity. Comparison with a conventional method was done so as to evaluate its performance. Simulation results have shown that the maximum contour error can be reduced by 50.26%.