A Distributed Optimization-Based Approach for Hierarchical MPC of Large-Scale Systems with Coupled Dynamics and Constraints

Reference

M. D. Doan, T. Keviczky, and B. De Schutter, "A distributed optimization-based approach for hierarchical MPC of large-scale systems with coupled dynamics and constraints," Proceedings of the 2011 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC), Orlando, Florida, pp. 5236-5241, Dec. 2011.

Abstract

We present a hierarchical MPC approach for large-scale systems based on dual decomposition. The proposed scheme allows coupling in both dynamics and constraints between the subsystems and generates a primal feasible solution within a finite number of iterations, using primal averaging and a constraint tightening approach. The primal update is performed in a distributed way and does not require exact solutions, while the dual problem uses an approximate subgradient method. Stability of the scheme is established using bounded suboptimality.

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BibTeX

@inproceedings{DoaKev:11-039,
   author    = {Doan, Minh Dang and Keviczky, Tam{\'a}s and De Schutter, Bart},
   title     = {A Distributed Optimization-Based Approach for Hierarchical
                {MPC} of Large-Scale Systems with Coupled Dynamics and
                Constraints},
   booktitle = {Proceedings of the 2011 50th IEEE Conference on Decision and
                Control and European Control Conference (CDC-ECC)},
   address   = {Orlando, Florida},
   pages     = {5236--5241},
   month     = dec,
   year      = {2011}
   }


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