State-space approach to interpolation in MPC

Interpolation between unconstrained optimal input trajectories and feasible trajectories forms the basis for a computationally efficient predictive control algorithm but lacks robustness in that uncertainty can destroy the guarantee of feasibility. To overcome this problem it is possible to introduce into the interpolation process a further input trajectory which is referred as 'mean level'.(2) This has been accomplished in an input-output setting and the purpose of the present paper is to show that it is possible to get a considerably simpler algorithm by recasting the problem into state-space form. Copyright (C) 2000 John Wiley & Sons, Ltd.