Feedback-aided iterative learning control

This paper presents feedback-aided iterative learning control strategies for linear time-invariant systems. Sufficient conditions of convergence of the feedback-aided PD-type learning algorithm are derived, and the converged output trajectory is given. The initial rectifying action is applied to eliminate the effect of initial shifts. It is shown that the system output converges to the desired one over the pre-scribed finite interval, whatever value the initial error takes but fixed. Numerical results are presented to demonstrate effectiveness of the proposed learning control schemes.