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

Leo Emil Sokoler, Gianluca Frison, Anders Skajaa, Rasmus Fogtmann Halvgaard, John Bagterp Jørgensen

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

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
Publication statusPublished - 2015

Keywords

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

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