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

@inproceedings{DoaKev:11-022,
   author    = {Doan, Minh Dang and Keviczky, Tam{\'a}s and De Schutter, Bart},
   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}
   }


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