Adaptive Iterative Learning Control Mechanism for Nonlinear Systems subject to High-Order Internal Model - Zhou, Wei; Yu, Miao (2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS), 2018)
This technical note addresses an adaptive iterative learning control (AILC) problem for nonlinear dynamical systems with partially unknown iteration-varying parameter. Referring to the scheme of state-space, an AILC effort is presented for randomly varying reference tracking together with initial shift problem in iteration domain. Furthermore, the AILC technique is extended to systems with several parameters in discussion. A simulation example confirms the validity of the proposed method.