Iterative Learning Control of a Parallel Delta Robot

In this work, an iterative learning control (ILC) is applied to a Delta robot in order to improve the tracking precision at high dynamic movement. Delta robot is a parallel manipulator designed for high-speed pick and place operations. Since the dynamic of Delta robot is highly coupled and nonlinear, the conventional controller like the proportional derivative (PD) failed to satisfy the required performances. To solve this problem a suitable controller for repetitive pick and place operations represents in the ILC has been introduced. The learning controller is combined with a PD controller to improve the tracking error through the iterations. Numerous simulations and robustness tests are carried out to demonstrate the effectiveness of the proposed scheme.