An off-line MPC scheme for discrete-time linear parameter varying systems

Abstract

An off-line Model Predictive Control (MPC) method based on ellipsoidal calculus and viability theory is described in order to address feedback regulation problems for input-saturated multi-model Linear Parameter Varying (LPV) systems. In order to reduce the computational burdens and the conservativeness of traditional robust MPC schemes, the proposed approach makes use of a scheduling linear control law which is based on a tighter refinement of the state trajectories tube. The control inputs are on-line obtained as the solutions of simple and numerically low-demanding optimization problems subject to set-membership constraints. The measurable plant parameters are directly used for feedback purposes. A numerical example is presented in order to show the benefits of the proposed regulation strategy and contrasted with a robust paradigm (the LPV hypothesis is not taken into account) and with a fast MPC algorithm for LPV systems which exploits a more traditional and conservative refinement of the state trajectory tube.