“Explicit Approaches to Constrained Model Predictive Control: A Survey”

Authors: Alexandra Grancharova and Tor A. Johansen,
Affiliation: Bulgarian Academy of Sciences and NTNU, Department of Engineering Cybernetics
Reference: 2004, Vol 25, No 3, pp. 131-157.

Keywords: Model predictive control, constraints, multi-parametric quadratic programming, pieceuwise linear controllers

Abstract: This paper presents a review of the explicit approaches to constrained model predictive control. The main motivation behind the explicit solution is that it avoids the need for real-time optimization, and thus allows implementation at high sampling frequencies in real-time systems with high reliability and low software complexity. The paper is organized as follows. Section 1 includes formulation of the constrained linear quadratic regulation (LQR) problem, summary of the implicit approaches, and the basics of the model predictive control (MPC). Sections 2 and 3 consider respectively the exact and the approximate approaches to explicit solution of constrained MPC problems, together with several examples.

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DOI forward links to this article:
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  title={{Explicit Approaches to Constrained Model Predictive Control: A Survey}},
  author={Grancharova, Alexandra and Johansen, Tor A.},
  journal={Modeling, Identification and Control},
  publisher={Norwegian Society of Automatic Control}