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Explicit Model Predictive Control

Encyclopedia of Systems and Control

Abstract

Model predictive control (MPC) has been used in the process industries for more than 30 years because of its ability to control multivariable systems in an optimized way under constraints on input and output variables. Traditionally, MPC requires the solution of a quadratic program (QP) online to compute the control action, often restricting its applicability to slow processes. Explicit MPC completely removes the need for on-line solvers by precomputing the control law off-line, so that online operations reduce to a simple function evaluation. Such a function is piecewise affine in most cases, so that the MPC controller is equivalently expressed as a lookup table of linear gains, a form that is extremely easy to code, requires only basic arithmetic operations, and requires a maximum number of iterations that can be exactly computed a priori.

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Authors and Affiliations

  1. IMT Institute for Advanced Studies Lucca, Piazza San Ponziano 6, 55100, Lucca, Italy

    PhDAlberto Bemporad

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  1. PhDAlberto Bemporad
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Correspondence to PhDAlberto Bemporad .

Editor information

Editors and Affiliations

  1. Electrical and Computer Engineering, Boston University, Boston, Massachusetts, USA

    John Baillieul

  2. Automation and Control Solutions, Honeywell, Golden Valley, Minnesota, USA

    Tariq Samad

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© 2013 Springer-Verlag London

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Bemporad, P. (2013). Explicit Model Predictive Control. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5102-9_10-1

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  • DOI: https://doi.org/10.1007/978-1-4471-5102-9_10-1

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  • Online ISBN: 978-1-4471-5102-9

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Chapter history

  1. Latest

    Explicit Model Predictive Control
    Published:
    14 September 2019

    DOI: https://doi.org/10.1007/978-1-4471-5102-9_10-2

  2. Original

    Explicit Model Predictive Control
    Published:
    20 March 2014

    DOI: https://doi.org/10.1007/978-1-4471-5102-9_10-1

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