A Difference Based Efficient Approximate Algorithm for Model Predictive Control of Input Constrained Linear Systems

Abstract

This paper proposes a novel efficient algorithm for model predictive control (MPC) of discrete-time linear systems subject to input constraints. As is well known, the MPC problem is reduced into the problem of calculating the solution trajectory of the discrete-time linear complementarity (D-LC) systems. Based on this fact, the algorithm fully exploits the information on the solution of the problem at the previous time step, as like the difference technique used in the calculation of the solution trajectory of the dynamical system. Efficiency of the proposed algorithm is shown by a numerical example.