A dual decomposition-based optimization method with guaranteed primal feasibility for hierarchical MPC problems


Reference:
M.D. Doan, T. Keviczky, and B. De Schutter, "A dual decomposition-based optimization method with guaranteed primal feasibility for hierarchical MPC problems," Proceedings of the 18th IFAC World Congress, Milan, Italy, pp. 392-397, Aug.-Sept. 2011.

Abstract:
We present a gradient-based dual decomposition method that is suitable for hierarchical MPC of large-scale systems. The algorithm generates a primal feasible solution within a finite number of iterations and solves the problem by applying a hierarchical conjugate gradient method in each dual iterative ascent step. The proposed scheme uses constraint tightening and a suboptimality bound to ensure stability and feasibility in a hierarchical MPC problem.


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Bibtex entry:

@inproceedings{DoaKev:11-022,
        author={M.D. Doan and T. Keviczky and B. {D}e Schutter},
        title={A dual decomposition-based optimization method with guaranteed primal feasibility for hierarchical {MPC} problems},
        booktitle={Proceedings of the 18th IFAC World Congress},
        address={Milan, Italy},
        pages={392--397},
        month=aug # {--} # sep,
        year={2011},
        doi={10.3182/20110828-6-IT-1002.03058}
        }



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