Robust predictive control for linear systems subject to norm-bounded model uncertainty

A novel robust predictive control algorithm is presented for input-saturated uncertain discrete-time linear systems described by structured norm-bounded uncertainties. The solution is based on the minimization, at each time instant, of an LMI convex optimization problem obtained by a recursive use of the S-procedure. Stability and feasibility are proved and comparisons with robust multi-model (polytopic) MPC algorithms are reported.