Robust Adaptive Model Predictive Control with Uncertainty Compensation for Linear Systems with Matched and Unmatched Uncertainties

This paper presents a robust adaptive model predictive control (MPC) framework that leverages an L1 adaptive controller to compensate for matched uncertainties and provide guaranteed uniform bounds on the error between the states and control inputs of the actual system and a nominal system. These bounds are then used to tighten the state and control constraints of the actual system, and an MPC is designed for the nominal system with the tightened constraints.