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Scalable MPC Design

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Handbook of Model Predictive Control

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Abstract

This chapter is devoted to decentralized and distributed MPC architectures for cyberphysical systems composed of subsystems that can be added or removed over time. We focus on MPC design approaches where the synthesis of a local controller requires, at most, pieces of information from parent subsystems, while preserving collective properties such as stability and satisfaction of constraints. In these methods the complexity of MPC design for a subsystem scales with the number of its parents only, rather than the overall system size. In particular, we review plug-and-play synthesis algorithms where the addition and removal of subsystems can be automatically denied if unsafe for the whole system. We provide a tutorial description of the main theoretical concepts behind scalable and plug-and-play MPC, as well as a review of the main approaches available in the literature. Design methods are also illustrated through applications to power network systems and fleets of electric vehicles.

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Notes

  1. 1.

    See, for example, [20] for an overview of distributed optimization methods.

  2. 2.

    Tie-line powers are shown in Chapter 9 in [22].

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Acknowledgements

The material in Section 6.2 is based on the work of Caroline Le Floch and we are grateful for making the simulation results available.

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Correspondence to Giancarlo Ferrari-Trecate .

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Farina, M., Ferrari-Trecate, G., Jones, C., Riverso, S., Zeilinger, M. (2019). Scalable MPC Design. In: Raković, S., Levine, W. (eds) Handbook of Model Predictive Control. Control Engineering. Birkhäuser, Cham. https://doi.org/10.1007/978-3-319-77489-3_12

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  • DOI: https://doi.org/10.1007/978-3-319-77489-3_12

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