In this article, a robust learning model-predictive controller (LMPC) for uncertain systems performing iterative tasks is presented. At each iteration of the control task, closed-loop state, input, and cost are stored used in design. This article first illustrates how to construct invariant sets safe policies exploiting historical data. Then, we propose an LMPC design procedure, where data gene...

A model predictive control algorithm based on offline optimization of prediction dynamics enables an efficient online computation. However, the price for this efficiency is a reduction in degree optimality. This article presents new method overcoming weakness, yielding significant improvement optimality, and achieving with no increase computational load. Two numerical examples comparison to ear...