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Towards Computational Complexity Certification for Constrained MPC Based on Lagrange Relaxation and the Fast Gradient Method

Author(s):

S. Richter, M. Morari, C.N. Jones
Conference/Journal:

Conference on Decision and Control (CDC), Orlando, USA, pp. 5223-5229
Abstract:

This paper discusses the certification of Nesterov's fast gradient method for problems with a strongly convex quadratic objective and a feasible set given as the intersection of a parametrized affine set and a convex set. For this, we derive a lower iteration bound for the solution of the dual problem that is obtained from a partial Lagrange Relaxation and propose a new constant step-size rule that we prove to be optimal under mild assumptions. Finally, we apply the certification procedure to a constrained MPC problem and show that the new step-size rule improves performance significantly.

Year:

2011
Type of Publication:

(01)Article
Supervisor:

M. Morari

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% Autogenerated BibTeX entry
@InProceedings { RicMor:2011:IFA_3870,
    author={S. Richter and M. Morari and C.N. Jones},
    title={{Towards Computational Complexity Certification for
	  Constrained MPC Based on Lagrange Relaxation and the Fast
	  Gradient Method}},
    booktitle={Conference on Decision and Control (CDC)},
    pages={5223--5229},
    year={2011},
    address={Orlando, USA},
    month=dec,
    url={http://control.ee.ethz.ch/index.cgi?page=publications;action=details;id=3870}
}
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