A framework for robustness analysis of constrained finite receding horizon control

A framework for robustness analysis of input constrained nite receding horizon control is presented. Under the assumption of quadratic upper bounds on the nite horizon costs, we derive suucient conditions for robust stability of the standard discrete-time linear-quadratic receding horizon control formulation. This is achieved by recasting conditions for nominal and robust stability as an implication between quadratic forms, lending itself to S-procedure tools which are used to convert robustness questions to tractable convex conditions. Robustness with respect to plant/model mismatch as well as for state measurement error is shown to reduce to the feasibility of linear matrix inequalities. Simple examples demonstrate the approach.