Adaptive iterative learning control for continuous systems with non-repetitive uncertainties and unknown state delays

This paper is devoted to tracking control of nonlinear multiple-input multiple-output systems subject to unknown state delays and non-repetitive uncertainties. An adaptive iterative learning control scheme is proposed by integrating a P-type feedback term, an iterative updating term and an additional compensation term. Among these terms, the first one is to alleviate the ill effect caused by non-repetitive uncertainties and the third one is utilized to handle the unwell learned part. The composite energy function methodology is employed to elaborate the bounded convergence of the tracking error. The validity of the proposed method is compared with existing results via simulation studies.