Iterative Learning Control for Nonlinear Systems With Iteration-Varying Trial Lengths Using Modified Reference Trajectories

In this work, a nonlinear uncertain system's iterative learning control (ILC) with randomly varying iteration lengths is discussed. Based on existing adaptive iterative learning control schemes, by using a modified reference trajectory, instead of assuming the identical initial condition, the alignment condition which is widely used in ILC problems can be satisfied when the iteration lengths is not fixed. An illustrative example is presented in the end to demonstrate the convergence of tracking error.