Design and Analysis of Adaptive Iterative Learning Control for Iteration-varying Nonlinear Systems

Design of iterative learning controller for continuous-time nonlinear systems with iteration-varying uncertainties is studied in this paper. The iteration-varying uncertainties include initial resetting tracking error, iteration-varying external disturbance, iteration-varying desired trajectory and iteration-varying system parameters. The iteration-varying uncertainties are not required to take any special structure and the uncertain bounds are not necessarily small. All the iteration-varying uncertainties are compensated by an adaptive iterative learning controller with a projection-type adaptive law. We show that the system output can converge to the desired one as close as possible after suitable numbers of learning trials. Compared with the existing papers studying the similar problems, this approach can be used to solve the iterative learning control issue with more general class of nonlinear uncertain systems and achieve better learning performance.