Encyclopedia of Systems and Control

Living Edition
| Editors: John Baillieul, Tariq Samad

Explicit Model Predictive Control

  • Alberto BemporadEmail author
Living reference work entry

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

Abstract

Model predictive control (MPC) has been used in the process industries for more than 40 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, sometimes restricting its applicability to slow processes. Explicit MPC completely removes the need for online 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.

Keywords

Constrained control Embedded optimization Model predictive control Multiparametric programming Quadratic programming 
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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.IMT Institute for Advanced Studies LuccaLuccaItaly

Section editors and affiliations

  • James B. Rawlings
    • 1
  1. 1.Dept. of Chemical EngineeringUniversity of CaliforniaSanta BarbaraUSA