Iterative Learning Control with Switching Gain PD feedback for nonlinear systems

In this paper, we propose a new iterative learning control called Switching Gain PD-PD (SPD-PD) Type Iterative Learning Control for trajectory tracking of time varying, nonlinear systems with uncertainty and disturbance. In the developed control scheme a PD feedback control with switching gains on iteration domains and a PD type iterative learning control, based on previous iterations, combines tracking errors into the updated law. It is proven that the boundedness of the final tracking error is guaranteed in the presence of uncertainty, disturbance, and initialization error. The convergence speed is adjustable by the adoption of the switching gains in the iteration domain. It is shown that a fast convergence and a small tracking error bound can be observed by using the SPD-PD type iterative learning control.