Learning control for non-parametric uncertainties with new convergence property [Brief Paper]

In this study, a learning control (LC) with state feedback is proposed for a class of non-linear systems with non-parametric uncertainties to track periodic trajectory. The proposed method offers a better convergence property than other LC methods, that is, the tracking error is bounded by an envelope monotonically decreasing to zero. It also links the controller parameters to the sum of total tracking error over the entire time horizon, thus it provides an explicit way to design the controller with respect to the control performance.