Iterative learning control for piecewise arc path tracking with validation on a gantry robot manufacturing platform

The piecewise arc path tracking problem is a common feature of manufacturing systems operating in a repetitive mode, e.g. assembly production lines. Here, the system end-effector must follow a spatial path without any specific temporal tracking constraints, which makes the temporal profile not fixed a priori. The technique of iterative learning control (ILC) is well-suited to handle this problem, since compared to classical feedback control methods, ILC is capable of learning from previous trial information to minimize the tracking error over repeated trials. This paper extends the ILC task description to address piecewise arc path tracking tasks, and further formulates a more general design framework than existing spatial ILC approaches. A comprehensive ILC algorithm is designed to handle this class of piecewise arc path tracking problems, and practical implementation instructions are provided. Validation is conducted on a gantry robot manufacturing testbed to confirm its feasibility and efficiency in practice with a comparison to existing methods showing its higher path tracking accuracy.