A Homogeneous and Self-Dual Interior-Point Linear Programming Algorithm for Economic Model Predictive Control

Publication: Research - peer-reviewJournal article – Annual report year: 2015

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We develop an efficient homogeneous and self-dual interior-point method (IPM) for the linear programs arising in economic model predictive control of constrained linear systems with linear objective functions. The algorithm is based on a Riccati iteration procedure, which is adapted to the linear system of equations solved in homogeneous and self-dual IPMs. Fast convergence is further achieved using a warm-start strategy. We implement the algorithm in MATLAB and C. Its performance is tested using a conceptual power management case study. Closed loop simulations show that 1) the proposed algorithm is significantly faster than several state-of-the-art IPMs based on sparse linear algebra, and 2) warm-start reduces the average number of iterations by 35-40%.
Original languageEnglish
JournalI E E E Transactions on Automatic Control
VolumePP
Issue number99
Number of pages6
ISSN0018-9286
DOIs
StatePublished - 2015
CitationsWeb of Science® Times Cited: 0

    Keywords

  • Optimization algorithms, Linear programming algorithms, Predictive control for linear systems, Riccati iterations, Energy systems
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