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Distributed MPC for Large-Scale Systems

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Handbook of Model Predictive Control

Part of the book series: Control Engineering ((CONTRENGIN))

Abstract

This chapter presents the main approaches to the design of Distributed Model Predictive Control (DMPC) algorithms. For simplicity, focus is placed on the control of linear, time-invariant, discrete time systems. Emphasis is initially given to the system and problem partitioning, and a discussion is reported on how the adopted decomposition strongly influences the properties of the control scheme in terms of minimality of the representation, descriptive capabilities of the model, and information transmission requirements. Then, after a short discussion on decentralized MPC, a taxonomy of DMPC methods is proposed and some prototype DMPC algorithms are described with the aim to highlight the main characteristics of the classes of methods nowadays available. In the final part of the chapter, the most promising directions of research in the field are briefly summarized, and the most interesting fields of application of DMPC are listed.

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Authors and Affiliations

  1. Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, via Ponzio 34/5, 20133, Milano, Italy

    Marcello Farina & Riccardo Scattolini

Authors
  1. Marcello Farina
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  2. Riccardo Scattolini
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Correspondence to Riccardo Scattolini .

Editor information

Editors and Affiliations

  1. Independent Researcher, London, UK

    Saša V. Raković

  2. Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA

    William S. Levine

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Farina, M., Scattolini, R. (2019). Distributed MPC for Large-Scale Systems. 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_11

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  • DOI: https://doi.org/10.1007/978-3-319-77489-3_11

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  • Publisher Name: Birkhäuser, Cham

  • Print ISBN: 978-3-319-77488-6

  • Online ISBN: 978-3-319-77489-3

  • eBook Packages: EngineeringEngineering (R0)

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