Robust Iterative Learning Model Predictive Control for Uncertain Nonlinear Systems with Time Delays

This study aims at the robust iterative learning model predictive control (ILMPC) for uncertain nonlinear systems with time delays. In order to achieve the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$H_{\infty}$</tex> tracking performance, a novel robust ILMPC scheme is designed based on the two-dimensional (2-D) system theory. To deal with the unknown time delays, an appropriate Lyapunov-Krasovskii functional is constructed, and the stability conditions are derived using linear matrix inequalities (LMIs). Furthermore, a new control gain determination strategy is introduced to improve the efficiency of the proposed ILMPC method. The effectiveness is verified through numerical simulations.