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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