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Handbook of Model Predictive Control pp 145–167Cite as

Birkhäuser

Economic Model Predictive Control: Some Design Tools and Analysis Techniques

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Abstract

In recent years, Economic Model Predictive Control has emerged as a variant of traditional (tracking) MPC which aims at maximizing economic profitability by directly minimizing, over a receding prediction horizon, the costs incurred in system’s operation. Several design alternatives have been proposed in the literature, as well as suitable tools for the analysis of stability and performance of the different design methods. This note provides the authors’ perspective on some of the most relevant results that appeared within this framework as well as, for interested readers, references to the technical papers where such results have first been discussed.

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Author information

Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Imperial College London, Exhibition Road, SW7 2AZ, London, UK

    David Angeli

  2. Dip. di Ingegneria dell’Informazione, Università di Firenze, Firenze, Italy

    David Angeli

  3. Institute for Systems Theory and Automatic Control, University of Stuttgart, 70550, Stuttgart, Germany

    Matthias A. Müller

Authors
  1. David Angeli
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  2. Matthias A. Müller
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Corresponding author

Correspondence to David Angeli .

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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Angeli, D., Müller, M.A. (2019). Economic Model Predictive Control: Some Design Tools and Analysis Techniques. 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_7

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  • DOI: https://doi.org/10.1007/978-3-319-77489-3_7

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  • Publisher Name: Birkhäuser, Cham

  • Print ISBN: 978-3-319-77488-6

  • Online ISBN: 978-3-319-77489-3

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