Abstract
In this chapter, a hierarchical model predictive control framework is presented for a network of subsystems that are submitted to general resource sharing constraints. The method is based on a primal decomposition of the centralized open-loop optimization problem over several subsystems. A coordinator is responsible of adjusting the parameters of the problems that are to be solved by each subsystem. A distributed-in-time feature is combined with a bundle method at the coordination layer that enables to enhance the performance and the real-time implementability of the proposed approach. The scheme performance is assessed using a real-life energy coordination problem in a building involving 20 zones that have to share a limited amount of total power.
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Acknowledgments
This work is part of HOMES collaborative program. This program is funded by OSEO.
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Lamoudi, M., Alamir, M., Béguery, P. (2014). A Distributed-in-Time NMPC-Based Coordination Mechanism for Resource Sharing Problems. In: Maestre, J., Negenborn, R. (eds) Distributed Model Predictive Control Made Easy. Intelligent Systems, Control and Automation: Science and Engineering, vol 69. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7006-5_9
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DOI: https://doi.org/10.1007/978-94-007-7006-5_9
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