Novel adaptive iterative learning control design targeting unknown time-delays and non-square control gains - Shen, Ruohan; Li, Xuefang; Li, Xiao-Dong (Journal of the Franklin Institute, 2025)
This work aims at the adaptive iterative learning control (AILC) design for a class of nonlinear systems subject to unknown non-square control gains and unknown time-delays. Based on the newly introduced model transformation technique, the unknown non-square control gain matrix is transformed into a norm-bounded uncertainty. Then the AILC scheme is developed based on the modified system dynamics, which is also effective in dealing with the unknown time-delays. Furthermore, based on the proposed design framework, a unified AILC strategy is developed, which is widely applicable to both square and non-square nonlinear systems. The convergence of the proposed AILC approach is analyzed rigorously by applying the Lyapunov-Krasovskii-like composite energy function (CEF) method, and the effectiveness is illustrated via numerical examples.