Technical communique: Improvements in the efficiency of linear MPC

Authors:
Shuang Li;Basil Kouvaritakis;Mark Cannon
Affiliations:
Department of Engineering Science, University of Oxford, OX1 3PJ Parks Road, Oxford, UK;Department of Engineering Science, University of Oxford, OX1 3PJ Parks Road, Oxford, UK;Department of Engineering Science, University of Oxford, OX1 3PJ Parks Road, Oxford, UK
Venue:
Automatica (Journal of IFAC)
Year:
2010

Citing 4
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Abstract

A model predictive control (MPC) strategy based on augmented autonomous predictions enables a highly efficient online optimization by imposing a terminal constraint at the current time. Near-optimal performance is obtained by delaying the imposition of the terminal constraint by one sampling period. However, under certain conditions the degree of optimality can be affected. An extension is proposed to remove this difficulty, yielding significant improvements in the degree of optimality, and achieving this at modest computational cost.