Combined Predictive and Feedback Contour Error Control With Dynamic Contour Error Estimation for Industrial Five-Axis Machine Tools
Yang Liu, Min Wan, Qun-Bao Xiao, Xue-Bin Qin
Abstract
This article proposes a real-time method to control the contour error for industrial five-axis machine tools by combining the generalized predictive control (GPC) and the feedback correction (FBC) with dynamic contour error estimation (CEE). The CEE is developed by well considering the curve’s curvature and torsion based on Taylor series expansion and Frenet frame theory. By utilizing the spherical linear interpolation, the tool orientation and the tool tip position are synchronized with respect to the curve length. A novel dynamic foot point searching procedure is established to weaken the influences of the tracking errors’ magnitude on the CEE precision. To tackle the transmission effect, the GPC is adopted to predict the servo systems’ outputs, and then, the induced tool pose deviations, which are subsequently utilized to counteract the contour errors, are predicted by constructing Jacobian matrixes. Especially, the FBC loops are constructed to suppress the influences of disturbances and further to reduce the magnitudes of contour errors. Simulations and experiments are conducted to verify the effectiveness of the proposed methods.