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 entry

@inproceedings{DoaKev:11-039,
author={M.D. Doan and T. Keviczky and B. {D}e Schutter},
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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