Adaptive Iterative Learning Control for High-Order Fully Actuated Nonlinear Systems with Parametric Uncertainties

In this paper, a novel adaptive iterative learning control (AILC) scheme is proposed for high-order fully actuated systems (HOFASs) with parametric uncertainties, where the convergence of the tracking error is analyzed under the framework of the composite energy function method. Moreover, by applying the backstepping, the proposed AILC method is extended to strict-feedback HOFASs (SFHOFASs), which widens the application scope of AILC significantly. Finally, two illustrative examples are presented to verify the effectiveness of the proposed AILC scheme.