Robust constrained model predictive control with persistent model adaptation

In this paper we present a novel approach for robust model predictive control (MPC) for constrained linear discrete-time systems with bounded time-varying structural uncertainties. The proposed method combines a dead-beat observer with a robust tube-based MPC for plants with structural uncertainties in the model, in order to persistently learn in finite time the uncertainties by using only input and output measurements of the plant. The time-varying uncertainties are assumed to satisfy a dwell-time constraint, and under the given assumptions recursive feasibility as well as asymptotic stability for the closed-loop system are established.