| 要約: | 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.
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