A Synthesis Approach of Constrained Robust Model Predictive Control

A synthesis approach of constrained robust model predictive control (SCRMPC) for systems with polytopic description is proposed. This proposal uses time-varying sequences of models in a polytope to forecast the model uncertainties and optimizes the terminal constrained set, the local controller and the terminal cost on-line. Using standard techniques, the problem is reduced to a convex optimization involving linear matrix inequalities (LMIs). We compare the proposed algorithm with the existing algorithms via an example and the simulation results demonstrate that our algorithm enlarges the feasible region and improves the control performance.