Document Type
Article
Publication Date
8-19-2021
Department
College of Computing
Abstract
Convex optimization solvers are widely used in the embedded systems that require sophisticated optimization algorithms including model predictive control (MPC). In this paper, we aim to reduce the online solve time of such convex optimization solvers so as to reduce the total runtime of the algorithm and make it suitable for real-time convex optimization.We exploit the property of the Karush–Kuhn–Tucker (KKT) matrix involved in the solution of the problem that only some parts of the matrix change during the solution iterations of the algorithm. Our results show that the proposed method can effectively reduce the runtime of the solvers.
Publication Title
IEEE Access
Recommended Citation
Iqbal, Z.,
Nooshabadi, S.,
Yamazaki, I.,
Tomov, S.,
&
Dongarra, J.
(2021).
Exploiting Block Structures of KKT Matrices for Efficient Solution of Convex Optimization Problems.
IEEE Access, 116604-116611.
http://doi.org/10.1109/ACCESS.2021.3106054
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/15396
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Version
Publisher's PDF