Precision LARC motion control of an industrial biaxial mechatronic system for complex contours based on a generalized GTCF coordination mechanism

In this paper, to simultaneously meet the challenge of complex high-speed large-curvature contouring tasks and high-performance motion control accuracy, a generalized global task coordinate frame (GTCF) based learning adaptive robust control (LARC) strategy is synthesized for biaxial mechatronic motion systems. The generalized GTCF is globally defined based on a constructed equivalent shape function of the desired contour, and can guarantee the multi-axes coordination to deal with high-speed large-curvature contouring tasks even under complex contours. After transforming the system dynamics of an industrial biaxial mechatronic motion system into the generalized GTCF, a LARC contouring controller is constructed for the strongly coupled nonlinear dynamics in each coordinate to achieve excellent contouring motion performance. In LARC, adaptive model compensation term and robust term are utilized to deal with parametric variation and uncertain disturbances respectively. With reasonable weight allocation of contouring error and distance error, iterative learning term is designed to address the unmodelled repetitive contouring error. Comparative experiments are carried out to demonstrate that the generalized GTCF-LARC can successfully implement various complex contouring tasks. Furthermore, comparing with conventional CCC and ARC control algorithm, the proposed generalized GTCF-LARC possesses strong coordination mechanism and excellent transient/steady-state contouring control performance.