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Ahead of Print article · Journal article

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

From

Department of Applied Mathematics and Computer Science, Technical University of Denmark1

Scientific Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark2

Ørsted A/S3

Dynamical Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark4

Center for Energy Resources Engineering, Centers, Technical University of Denmark5

CITIES - Centre for IT-Intelligent Energy Systems, Centers, Technical University of Denmark6

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%.

Language: English
Publisher: IEEE
Year: 2015
Pages: 1-1
ISSN: 23343303 , 00189286 and 15582523
Types: Ahead of Print article and Journal article
DOI: 10.1109/TAC.2015.2495558
ORCIDs: Halvgaard, Rasmus Fogtmann and Jørgensen, John Bagterp

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