An Accelerated Dual Gradient-Projection Algorithm for Embedded Linear Model Predictive Control

This paper proposes a dual fast gradient-projection method for solving quadratic programming problems that arise in model predictive control of linear systems subject to general polyhedral constraints on inputs and states. The proposed algorithm is well suited for embedded control applications in th...

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Bibliographic Details
Published inIEEE transactions on automatic control Vol. 59; no. 1; pp. 18 - 33
Main Authors Patrinos, Panagiotis, Bemporad, Alberto
Format Journal Article
LanguageEnglish
Published IEEE 01.01.2014
Subjects
Acceleration
Computational methods
Convergence
Equations
Optimization
optimization algorithms
Prediction algorithms
predictive control for linear systems
Tin
Vectors
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ISSN0018-9286
1558-2523
DOI10.1109/TAC.2013.2275667

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Summary:This paper proposes a dual fast gradient-projection method for solving quadratic programming problems that arise in model predictive control of linear systems subject to general polyhedral constraints on inputs and states. The proposed algorithm is well suited for embedded control applications in that: 1) it is extremely simple and easy to code; 2) the number of iterations to reach a given accuracy in terms of optimality and feasibility of the primal solution can be tightly estimated; and 3) the computational cost per iteration increases only linearly with the prediction horizon.
ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2013.2275667