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A Hierarchical Distributed MPC Approach: A Practical Implementation

  • A. Zafra-CabezaEmail author
  • J. M. Maestre
Chapter
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 69)

Abstract

This chapter presents a hierarchical distributed model predictive control algorithm. Two levels in the problem optimization are presented. At the lower level, a distributed model predictive controller optimizes the operation of the plant manipulating the control variables in order to follow the set-points. The higher level implements a risk management strategy based on the execution of mitigation actions if risk occurrences are expected. In this way it is possible to take into account additional relevant information so that better results are achieved in the optimization of the system.

Keywords

Model Predictive Control Insurance Contract Mitigation Action Prediction Horizon Manipulate Variable 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

Financial support from the HYCON2 EU-project from the ICT-FP7 and MEC-Spain, DPI2008-05818, and F.P.I. grants is gratefully acknowledged.

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.System Engineering and Automatic DepartmentUniversity of SevilleSevilleSpain

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