Abstract
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’. 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 © 2000 John Wiley & Sons, Ltd.
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