Horizon Adaptation for Nonlinear Model Predictive Controllers with guaranteed Degree of Suboptimality

Details Horizon Adaptation for Nonlinear Model Predictive Controllers with guaranteed Degree of Suboptimality Horizon Adaptation for Nonlinear Model Predictive Controllers with guaranteed Degree of Suboptimality

2011-05-16

arxiv.org/abs/1105.3037v1

Mathematics

Optimization and Control

20 pages, 3 figures

Scientific paper

We propose adaptation strategies to modify the standard constrained model predictive controller scheme in order to guarantee a certain lower bound on the degree of suboptimality. Within this analysis, the length of the optimization horizon is the parameter we wish to adapt. We develop and prove several shortening and prolongation strategies which also allow for an effective implementation. Moreover, extensions of stability results and suboptimality estimates to model predictive controllers with varying optimization horizon are shown.

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