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

Authors:	Saitou Yutaka, Tokyo Institute of Technology/JAPAN, Japan Imura Jun-ichi, Tokyo Institute of Technology/JAPAN, Japan
Topic:	2.4 Optimal Control
Session:	Optimal Control Theory and Design Methods
Keywords:	Prediction Control, Linear Complementarity Systems, Constrained Systems

Abstract

This paper proposes a novel efficient algorithm for model predictive control (MPC) of input-constrained linear systems. Based on the fact that the problem of MPC is reduced into the problem of calculating the solution trajectory of the discrete-time linear complementarity (D-LC) systems, the proposed 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 solution trajectories of a dynamical system. It is shown that the proposed algorithm is much more efficient than the other conventional algorithms at a large prediction horizon.