Stabilizing reduced order model predictive control for constrained linear systems

Abstract

This paper considers a stabilizing reduced order model predictive control for constrained linear discrete-time systems. By employing a system decomposition on the input-output function space, a reduced order model predictive control law, which guarantees closedloop stability and feasibility, is obtained from a low dimensional on-line optimization problem. Numerical examples are provided to illustrate the proposed method.