Parallelized Model Predictive Control
Name
DS_ACC2013_PMPC.pdf
Description
PMPC ACC2013
Size
494.45 KB
Format
Adobe PDF
Checksum (MD5)
468c7cbb6606a78cb32c0e787292638e
Author(s)
Soudbakhsh, Damoon
Annaswamy, Anuradha M.
Date Issued
June 2013
Journal
Proceedings of the 2013 American Control Conference
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Soudbakhsh, Damoon and Anuradha M. Annaswamy. "Parallelized Model Predictive Control." 2013 American Control Conference. IEEE, 2013.
Version
Author's final manuscript
Abstract
Model predictive control (MPC) has been used in many industrial applications because of its ability to produce optimal performance while accommodating constraints. However, its application on plants with fast time constants is difficult because of its computationally expensive algorithm. In this research, we propose a parallelized MPC that makes use of the structure of the computations and the matrices in the MPC. We show that the computational time of MPC with prediction horizon N can be reduced to O(log(N)) using parallel computing, which is significantly less than that with other available algorithms.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6580083
