Reduced Order Model Predictive Control Based on Decomposition of Discrete-time Linear Systems

Abstract

This paper deals with a reduced order model predictive control (MPC) for constrained discrete-time linear systems. By introducing a decomposition method for discrete-time linear systems with a quadratic cost functional, the pairs of initial state and input sequence which have a strong influence on input-output relation are clarified. Then an MPC law is obtained by solving a low-dimensional optimization problem. A numerical example is provided to illustrate the proposed method.