Trajectory tracking controller for nonlinear systems with disturbances using iterative learning algorithm without resetting condition

This paper presents an iterative learning scheme (PD-type) to solve the trajectory tracking problem for repetitive uncertain nonlinear systems. This scheme consists of two parts, the first is an iterative learning controller and the second is an algorithm which gives us the initial state at each trial. λ-norm method is used to prove the asymptotic stability of the closed loop system. Finally, we apply this controller scheme on perturbed nonlinear system to show its effectiveness.